September, 2018

AI & Big Data:Talent Landscape & assessment

Zinnov Point of View

22

There is a huge demand for Global AI & Big Data talent, and its set to impact global economies, markets and industries

1.a

~650,000

~265,000

~120,000

AI & Big Data/ Analytics Directly Relevant Talent

Directly Relevant Talent in G500 companies

Directly Relevant Talent in ITeS Service Providers (SPs)

Job openings across G500, Start-ups and SPs

Global AI & Big Data Talent pool Demand

Directly Relevant Talent in Start-ups

~515,000

~1.2 Mn

~270,000

Total Employed AI & BD/A talent pool

G500 companies

Global Start-Ups

Service Providers

Unmet AI & BD/A talent demand in

2018

Global Demand in 2018

1

2

Note: DRAUP Methodology, Numbers of graduating students are estimates and will vary by year

Note: Other engineering skills include Electronics, Electrical, communication, mechanical and engineering skills employed across Semiconductors, Telecommunication, IT & computer peripheral industry

*G500 Companies (Top 500 product organization by R&D spend)

Directly Relevant Talent Pool

Open Position Analysis

33

DRAUP Analysis Track: One of the key components of our methodology involves analysis of installed Big Data and AI workforce employed in G500* organizations, Start-ups and Service Providers

Source: DRAUP Methodology

Demand Side: Analysis Tracks

Skill Maturity Analysis

Job progression and

maturity assessment

Workloads

G500* Companies1.a

Talent distribution by Geo

Skill characteristics

Start-Up1.b Service Providers1.c

Installed Talent Pool

Skill Distribution by

Geography

Open job positions for bigdata analytics & DS

*G500 Companies (Top 500 R&D spenders)

44

Unique job roles : 7 Primary Skills and job roles were shortlisted and analysed within Big Data & Data Science engineering

Unique Roles Titles Technical or Conceptual Skills Description

Note : DRAUP’s proprietary talent module was used to analyse jobs by job roles and skill type

Analyst - Data Management

Maintains and manages the database;

Responsible for performing quality checks on

datasets; Ensures correct data schema and

syntax; Filters and cleans data"

Database Analyst, Data Management Analyst, Database Developer, Database Administrator

1.

Data Architect

Designs and implementing the technical

architecture; Defines and designs data

systems, services and technology solutions;

Implements and administers data

infrastructure

Data Architect, Tech Lead Data Platform, Tech Lead Data Modelling

2.

Big Data / Hadoop Administrator

Supports the Hadoop infrastructure and ensures

availability; Responsible for node-cluster

configuration, deployment and capacity planning;

Monitors and maintains clusters and tunes

performance; Responsible for administering

YARN and providing support for running and

monitoring MapReduce jobs

Creates data pipelines to move and transform data;

Responsible for performing transformations to

aggregate disparate data volumes into data lakes;

Manages data from different sources; Provides

support, maintenance, monitoring and

troubleshooting for data warehouse processes

Data Warehouse Engineer

Data Engineer, Data Warehouse Engineer, Data Warehousing Specialist, Data Developer, Hadoop Developer, Spark Developer, Hadoop Engineer, Spark Engineer, Scala Engineer, Scala Developer

Hadoop Administrator, Data Administrator, Big Data DevOps Engineer, Hadoop Platform Engineer

3.Database

Engineering

apache, azure, distribute systems,

flume, google cloud, gradle,

integrations, java j2ee,

database architecture, relational

databases, data cleaning, data

manipulation, tableau, power bi,

excel

hadoop, flume, YARN, mongodb,

dynamodb, mapreduce, devops,

hbase, hdfs, AWS

hbase, amazon web service,

kafka, spark, cassandra,

dynamodb, flume, gradle, graph,

hadoop, jmeter, json

Skill Definitions

55

Unique job roles : 7 Primary Skills and job roles were shortlisted and analysed within Big Data & Data Science engineering

Develops algorithms for conversational

interfaces such as chatbots; Identifies the

modes by which speech can be converted to

data; Develops conversational interfaces

using bot frameworks and platforms

Chatbot Developer, Chatbot Engineer, Conversational UI Specialist, Speech Scientist, Speech Researcher, Speech Algorithm Scientist, Speech Algorithm Engineer, Speech Algorithm Researcher, Machine Learning Engineer - Speech, Machine Learning Scientist - Speech, AI Engineer -Speech, AI Researcher - Speech, Machine Learning Engineer - Conversation, Machine Learning Scientist - Conversation, AI Engineer -Conversation, AI Researcher - Conversation

Applied Data Scientist - Speech

Note : DRAUP’s proprietary talent module was used to analyse jobs by job roles and skill type

Applied Data Scientist - Vision

Computer Vision Scientist, Computer Vision Engineer, Algorithm Engineer - Computer Vision, Computer Vision Engineer, ADAS Engineer, Vision Engineer, Perception Engineer, Deep Learning Scientist, Deep Learning Engineer

Develops algorithms for vision-based

applications such as image or object

recognition applications; Designs vision

algorithms for mapping, localization, scene

analysis, object detection and classification;

Develops a perception based solution

integrating multiple sensing devices within

the size, weight and power (SWaP)

5.Applied AI

Analyses and interprets data (both structured

and unstructured) and generates prescriptive

and predictive insights; Responsible for

generating insights from raw data using

inferential and predictive models; Responsible

for developing new analytical models for the

organization

Data Scientist, Applied Scientist, Data Researcher, Applied Researcher, Data Modeling Scientist, Data Modeling Specialist, Data Modeling Engineer, Data Mining Scientist, Data Mining Specialist, Data Mining Specialist, Algorithm Scientist, Algorithm Engineer, Algorithm Specialist, Machine Learning Scientist, Machine Learning Engineer, Machine Learning Researcher, NLP Scientist, NLP Researcher, NLP Engineer

Data Scientist4.

Unique Roles Titles Technical or Conceptual Skills Description

OpenCV, Tensorflow, Pandas, 3D

Modelling, Adaptive Thresholding,

Caffe, Convolutional Neural Network

Dialogflow, API.ai, Wit.ai, Microsoft

Bot Framework, Bayes Rule,

Bidirectional RNN, Chomsky

Hierarchy

Classification, clustering, decision trees,

dimensionality reduction, logistic

regression, SVM, natural language

process, predictive analytics,

Skill Definitions

66

AI & Big Data talent in US, China and Israel is predominantly employed by US based Tech Giants; Talent in Canada and UK is largely employed by start-ups; India has high talent pool installed among Service Providers

5%

9%

3%

52%

5%

0%

48%

60%

22%

20%

61%

21%

48%

32%

74%

28%

34%

79%

Canada

UK

China

India

US

Israel

G500 Companies

(Top 500 R&D spenders)

Start-Ups Companies

(0>Headcount>5000)Service Providers

295,000

152,000

67,000

28,000

18,000

AI & Big Data Installed Talent 2018 split by company type Insights

AI & Big Data talent in US is predominantly split between large companies and start-ups. Companies such asGoogle, Microsoft, Facebook IBM, etc. have large installed talent bases for AI & Big Data in US, led by Googlewith most of the Big Data Analytics work done out of US. Notable small and medium companies have come upsuch as Splunk, Cloudera, MongoDB who are becoming key infrastructure developers.

India’s Big Data talent is predominantly employed in large service provider companies, involved in solutions deployment and support services (IBM, Infosys, TCS etc..). Amazon, Microsoft and IBM Watson have a significant AI talent pool. Notable medium and small companies such as InMobi, Musigma use Big Data Analytics for Performance tracking of Mobile Ads and are key employers for analytics talent

China’s AI & Big Data talent is employed predominantly in large companies, both local and MNCs, such as Baidu, Tencent, Alibaba, EBay, Amazon etc.. Engineering teams with-in Deep learning start-ups such as i-CarbonX, SenseTime, Face++ have rapidly scaled during last 2 years

AI & Big Data talent in UK is significantly available in Start-ups largely focussed on industry applications. Tech giants such as Google (DeepMind), IBM(Watson healthcare) and Microsoft (Big Data Analytics for Bing and Skype) etc. large scale in-house engineering team grown through acquihires

Canada’s AI & Big Data talent pool has a large presence in start-ups and niche mid-sized companies such as Algolux, Instaclick (webpage and ad analytics). Large companies also employ a significant portion of the AI & Big Data talent such as Microsoft (Healthcare AI), IBM Watson (big data banking and finance back-end solutions) and EA Sports (gaming analytics),

14,000

G500 Companies Start-ups Services

AI & Big Data talent is largely engaged by Start-ups such as BrainQ, Iguazio etc. and Tech giants such asMicrosoft, Samsung and Google. Automotive OEM’s such as GM and Ford have engineering focus onautonomous and connected driving.

Note : DRAUP Talent module Analysis as well as skill analysis from job portals

Demand Analysis

77

Directly relevant talent across G500 organizations: Tier-1 US locations have nearly ~44% of total employed AI & Big Data talent pool consolidated within Tech giants

27,000

Seattle Area

56,000

Bay Area

5,000

Boston

10,000

New York11,000

Israel

9,000

UK

9,000

France

6,000

Spain

6,000

Sao Paulo

15,000

Germany

26,500

Bangalore

22,000

Beijing

9,200

Tokyo

2,400

Singapore

6,500

Hyderabad

Netherlands

20,000Shanghai

Employed AI & Big Data talent across global G500 companies

Note: DRAUP G500 skills mapping modeler – 2017, 2018 Generic AI Talent pool not considered as there is noise in the data

~250KDirectly relevant AI & Big Data talent in G500

companies

35%of the 250K employees are working for

Tech Giants

~110KDirectly relevant AI & Big Data talent in US

G500 Companies Start-ups Services

950

Employed AI & Big Data Talent Pool

88

~120,000

~40,000~23,000

~4500 ~22,000~28,000

Start-up Talent Overview: Indian and Chinese AI & Big Data start-ups have attracted late stage investments from global VCs and thus have rapidly scaled their engineering teams in last 2 years

CAGR: 5%

CAGR: 3.5%CAGR:46%

CAGR: 30%CAGR: 14%

Western US UK India ChinaEastern US Israel

• Chinese Deep learning start-ups such as iCarbonX, Face++,

Sensetime have attracted large late stage investments from

global VCs during last 2 years

• Indian start-ups such as Netrdyne, niki.AI and FluidAI have

also raised mid staged rounds and have been ramping up their

engineering team size

G500 Companies Start-ups Services

~5,5002018Number of AI & Big

Data start-ups

270K2018Total Directly

relevant talent

CAGR: 3.5%

Massively scaled deep learning

Data cataloguing and cleaning

AI based consumer robotics start-up

Key AI & Big Data Start-ups across global locations

ML based threat detection

NLP API

ML for retail

ML based recruitment solution

ML for personalised healthcare

Vision based advanced assistance system

Note : DRAUP’s Talent Simulation Module analysed 10,000+ start-ups globally to identify top AI & Big Data based start-ups

Employed AI & Big Data Talent Pool

2018

2016

~xxInstalled Talent

99

G500 Companies Start-ups Services

Global IT and Engineering Services giants have mature Big Data talent pool and have been upskilling employees to develop AI capability; Indian players hold up ~58% of total talent

Geo-Wise Talent Distribution across skills

• India accounts for more than 50%of the available talent in service providers.

• Service providers like TCS are

setting up CoE in collaboration with Intel to speed up adoption of AI.

• TCS and Infosys have developed their proprietary AI platforms to serve global customers

• Infosys provides mandatory training on Artificial Intelligence to new joiners.

• Tech Mahindra has tied up with Edxto reskill 117K employees in areas like Big Data, IoT, Machine Learning etc.

Big Data AI/ML

Directly relevant AI & Big

Data talent in India

~50K

~8K

Big Data AI/ML

Directly relevant AI & Big

Data talent in US & Canada

~9K~2K

Big Data AI/ML

Directly relevant AI & Big

Data talent in China

~2K

~0.5K

India

~58K

Total AI & Big Data directly relevant talent by delivery locations

~100K

US & Canada

~11K

China

~2.5K

Europe

~23K

Big Data AI/ML

Directly relevant AI & Big

Data talent in Europe

~19K

~3K

• Capgemini bagged the European Commission data infrastructure project.

• Insurance firm Direct Line Group appointed Capgemini for IT restructure.

• Atos has partnered with Google Cloud to create secure enterprise business solutions in Artificial Intelligence, Machine Learning, Hybrid Cloud, data analytics and the digital workplace.

• Atos and Siemens have committed 100M pounds for R&D in AI, Big Data, IoT and Cybersecurity.

• DXC Technology launched an Agile Process Automation (APA), which combines cloud and robotic process automation (RPA) with embedded artificial intelligence (AI) to enhance a company’s business processes.

• Cognizant has tied up with Goodwill University to impart training in Digital technologies and other IT courses.

• Avanade has tied up with Microsoft to create new AI-based solutions

• Avanade collaborated with Hortonworks to provide big data solutions to enterprises.

• Pactera launched an innovation outpost called Moonshot to lead global clients through the next era of digital products with a heavy emphasis on artificial intelligence, data and continuous software delivery paired with next generation human-centeredexperience design.

Note: Data curated by DRAUP engineering services deals database updated in April, 2018

Employed AI & Big Data Talent Pool

1010

23% 21% 19%24%

17% 20%

77% 79% 81%76%

83% 80%

India China UK Israel Canada US

ML

Big Data

~72,000 ~67,300 ~32,100 ~5,000 ~15,700 ~310,000

US, India, China and UK have the most number of job openings in AI & Big Data/Analytics

Top Recruiters

Job Titles

ML - Flipkart, Amazon, Accenture, Intel, Citi, AmazonBig Data - HP, HSBC, Citi, Accenture, Zebra Technologies, Lead Squared

ML - State street, Net ease, Google, Intel, HSBC, TeradataBig Data - Accenture, Intel, Baidu, Career International, NetEase, Michael Page, JD Group

ML - Data Scientist, Revolution Analytics, Test Architect, Research Scientist-Computer VisionBig Data - Applications Developer, Cloud Architect

ML - NLP Leader, Principal Software Engg, Chief Research ScientistBig Data - Data Management Engg, Test Automation Engg

ML - Hamham, Guardian Jobs, Amazon, Microsoft, Barclays, Hitachi, Expedia GroupBig Data - Burberry, Office of National Statistics, Olivier Bernard

ML - Senior data scientist, Full stack web develop, Data Analyst, Robotics EnggBig Data - Data Scientist, Data Development Officer

ML - Citi, Amazon, Google, Intel, General Motor, Nike, CiscoBig Data - Outbrain, Verac,

Outbrain, Kenshop, Midlink

ML - Full stack Developer, Software Engineer, System Team LeadBig Data - Business Research Analyst, Data Scientist

ML - Google, EY, Deloitte, Mark's, Synopsys, Uber, Capital OneBig Data - RBC, CIBC, Citi, Intact,

Newfound Recruiting

ML - Software Developer, Full stack Innovation Tech lead, Generalist Software developer, Data ScientistBig Data - Software Engineer

ML - JP Morgan, Intel Amazon, Google, Microsoft, NVIDIA, FacebookBig Data - IBM, Google, Microsoft, JP Morgan, Amazon Home Depot, Mclane

Company, Ring Central, Sirius XM

ML - Software Engineer, Applied Scientist, Manager, Product Design Engineering, Algorithm EngineerBig Data - Senior Data Architect, Senior Technical Architect

AI & Big Data Analytics global job opening distribution~515,000

Global Un-met Demand

Note: Data curated from global job portals such as LinkedIn, Indeed, Glassdoor etc.

1111

About 1 Million jobs are expected to be created in AI and Big Data/Analytics roles in 2021

0

1,00,000

2,00,000

3,00,000

4,00,000

5,00,000

6,00,000

2018 2019 2020 2021

AI Job Openings BD/A Job Openings

• Globally, Job Creation for AI & Big Data Analytics roles will reach 960K in 2021 with an average CAGR of 23%

• India is expected to grow at a faster rate (~25%) compared to the rest of the world

• The Job Creation for Big Data/Analytics roles will grow at a much lower rate (~7%) compared with AI over the next 3 years

~415K

~100K

~450K

~510K

India Job Openings – 2018

Big Data / Analytics – 55.5K

Artificial Intelligence – 16.5K

India Job Openings – 2021

Big Data / Analytics – 68K

Artificial Intelligence – 74K

Job Openings Projection

Global Job Openings

Note: Data curated from global job portals such as LinkedIn, Indeed, Glassdoor etc.

1212

Presence of heavyweights like IBM, GE, Microsoft, Amazon, etc. has helped create an AI/BD ecosystem in India. Amazon India, Walmart Labs have invested heavily on analysing Big Data sets generated by customer interactions acrossRetail, Seller Services and

leverage NLP algorithms to predict customer behaviour.

UK AI & Big Data talent is significantly engaged in large companies such as Google DeepMind group, IBM(Watson Health) and Microsoft (Big Data Analytics for Bing and Skype) etc.

Microsoft technical centre in Israel is working on Medical Imaging for predictive Eyecare.

Automotive OEM’s like Renault, Volkswagen partnering with Autonomous start-ups like Mobileye

MNCs such as GoogleDeepMind group, Microsoftand IBM Watson group havelarge scaled AI & Big Datalabs in Canada.Automotive OEMS such asFord, GM have set-up largeAI labs in Montreal andToronto to expandautonomous drivingresearch.

Majority of G500 organizations have employed Big Data talent across geographies; Computer Vision & NLP talent is employed majorly by tech giants

~43,000

AI and bigdata analytics Global G500 Talent distribution

Geo-Wise G500 Talent Distribution across skills

35%

42%

55%

41%

25%

16%

44%

20%

34%

7%10% 9% 8%

4% 4% 4% 5% 4%

11% 13% 11%

26%

15% 14%

22%16% 16%

31%34%

24% 23%

54%

64%

29%

56%

45%

16%

1% 1% 3% 3% 2% 1%3% 1%

West Coast East Coast Canada UK Germany Israel India China Singapore

Analyst-Data Management Data Architect Database Engineering Data Scientist Applied ML

~43,000 ~45,000~9,000 ~11,000~11,000~85,000 ~25,000 ~15,000 ~2,400

G500 Companies Start-ups Services

Traditional Hubs forEngineering for the TechGiants –Google, Amazon,Facebook, Apple andMicrosoft hold ~35% ofglobal G500 Big DataMachine learning to NLP &Computer vision talentDriverless Cars, Drones,Predictive medicine, CyberSecurity are the hot areas

China’s AI & Big Data Talent is employed predominantly in large companies, both local and MNCs, such as Baidu, Tencent, Alibaba, EBay, Amazon etc. Baidu is investing heavily in Visionfor Autonomous Driving and fleet route optimization by analyzing Mn of vehicle datasets.

Skill Analysis

Note : DRAUP’s Talent Simulation Module analysed jobs of ~2000 peer companies on the basis of skill type, salaries, talent pool, years of experience and employers

1313

Over 60% of the demand is distributed across Enterprise Software, Consumer Electronics and BFSI industries

LEGEND

Cell Colour

Concentration of Role in the Industry

14,000

12,000

37,000

102,000

16,000

22,000

39,000

7,000

Global Headcount

Big Data / Hadoop Admin

Analyst -Data

Management

Data Warehouse Engineer

Analyst -Business

Intelligence

Data Scientist

Visualization Specialist

Data Architect

Analyst -Information Security

Applied Data

Scientist -Speech

Applied Data

Scientist -Vision

Data Steward

Automotive

Healthcare

BFSI

Enterprise Software

Semiconductor

Retail

Consumer Electronics

Industrial

Note: For each vertical Map has to be read left to right

<1% 1% to 10% 10% to 25% 25% to 40% >40%

Total: 250k

1414

Data Warehouse EngineerIT Admin Data Scientist

Marketing Programs Manager

Research & Consulting

Data Scientist

Statistician Data Scientist

DataScientist

Statistician

Algorithms Developer/Engineer

DataScientist

Machine learning specialist

Algorithms Developer/Engineer

DataScientist

Data Scientist Job Progression: Business Analyst and Algorithms Engineer are the key roles which have progressed into Data Scientist role

Data Scientist Job Progression Roadmap

Previous Role Current RolePast Role

Business/DataAnalyst 1

Business/DataAnalyst 1

DataScientist

~24,000 Data Scientist profile analysed

across 10 Tech Giants*

~85% profiles

~15% profiles

Tech Giants*: Google, Facebook, Apple, Microsoft, Intel, Amazon, IBM, SAP, Salesforce, Cisco

Data WarehouseEngineer

Skill Analysis

DataScientist

Analyst1: System Analyst, Financial Analyst, Risk Analyst, Operations Analyst, IT Analyst, Support Analyst , Actuarial Analyst

Statistician

Area/Operations Manager

1515

Labor repurposing is becoming crucial and in many cases the only viable strategy

Statisticians/ Actuaries

Quantitative/Risk Analysts

Data Engineers

Data ScientistML

Engi

nee

r

Core Network Engineer

3G and LTE RF Engineer

End-to-End 3G/4G Network Engg

4G/LTE RAN Engineer

5G

En

gin

eer

Systems Engineer

Data Centre Engineer

Cloud Security Engineer

IOT Security Engineer

IOT

Engi

nee

r

Identify adjacent job roles with low degree of separations and upskill them

leveraging certification courses

Leverage expertise and skills of Veteran talent pool:

Numerous community colleges are offering specialized courses in new age

technologies

Community colleges offering Data Science Courses

UPSKILL EMPLOYEES LEVERAGE VETERAN TALENT POOL HIRE FROM COMMUNITY COLLEGES LEVERAGE WIDER GEOGRAPHIES

Information technology: Expertise Veterans offer: Advanced Training in analytics, information management, control systems and computing architectures

Healthcare Expertise Veterans offer: Up-to-date medical knowledge with extensive clinical experience

Engineering and ManufacturingExpertise Veterans offer: Education and training in mechanical, electrical and civil engineering, Distinctive project experience augmented by theoretical knowledge from schools

~11M employable Veteran talent pool is available in USA

Enterprises need to leverage Tier2 locations with high fresh talent pool

Top Emerging locations with high Fresh talent pool supply

Top Established locations with high Fresh talent pool supply

Los Angeles Baltimore

Minneapolis Tampa, Florida

Philadelphia Area Phoenix

San Diego Portland

Miami Raleigh Durham

Denver Columbus

Orlando Las Vegas

New York San Francisco

Chicago Houston

Boston Seattle

Washington DC Dallas

Austin Atlanta

Note : DRAUP’s proprietary talent module was used to analyse millennial moments across various citiesSource: Migration trends analysed using USA Census Data

1616

US: Employed Talent is consolidated across Tech giants and platform start-ups having large scale engineering labs focussed on cross industry application

2. Mature platform start-ups: Start-ups with

>100 Mn+ investment are concentrated in Bay Area with a focus on cross-functional industry platforms

1. Tech giants employ large scale AI/BD talent

pool concentrated in tier-1 locations~25,000 AI/BD engineers

employed

25 bn+AI/BD

Spend annually

100+Start-up Acquisitions

made globally

300+Platform start-ups

40%Deep Learning

20%NLP

10%Computer Vision

10%Robotics

GoogleFacebookAmazonApple

Microsoft

3. Mature University Ecosystem: MIT, NYU and

Stanford produce ~2000 fresh AI/ML talent pool

20+Tiet-1 Universities with PhD programmes in AI/Big Data

Facebook - NYU

Facebook hires NYU deep learning expert to run its AI lab

Amazon - UC Irvin

Amazon hires UC Irvine principal scientist to run its Deep learning AWS lab

Mature AI talent pool concentrated across Tech giants and Start-ups

Note : News articles, journals, university reports

Location Deep Dive : US

1717

Supply Drivers

Talent Quality Talent Scalability Cost Benefits

It has high quality Data science and AI talent

Average scalability due to average fresh

university talent supplyHigh talent cost due to

scarce AI talent

It is the emerging hub for AI & Big Data

analytics

High scalability fueled by researchers at local

universitiesHigh Talent cost for a

high talent quality

It has low AI talent and average Big data/

analytics talent

Average scalability due to average fresh

university talent supply

Low talent cost as most of the Dallas talents

are fresh talents

It has high DS/ Big data installed talent after

Bay area

High scalability options in Seattle due to

availability of university talent pool

Talent cost in Seattle is high due to intense

demand for ML expertise

It is an emerging locations for AI tech

companies

Average scalability due to average fresh

university talent supply

Low talent cost as most of Phoenix talents are

fresh talents

US: ~65% of AI & Big Data Talent in US is concentrated across Bay Area & Seattle; Central and Eastern region’s talent is largely spread across start-ups

Seattle

43%

57%Start-ups

Tech

Companies

63K+ Talent

22%

Others

14%

Bay Area

48%

52%Start-ups

Tech

Companies

110K+ Talent

39%

Phoenix

33%

67%Start-ups

Tech

Companies

9K+ Talent

3%

Dallas

29%

71%Start-ups

Tech

Companies

17K+ Talent

6%

Austin

60%

40%Start-ups

Tech

Companies

10K+ Talent

4%

Boston

24%

76%Start-ups

Tech

Companies

35K+ Talent

12%

~ 280,000AI/Big Data Talent

Bay Area

Boston

Dallas

Seattle

Phoenix

Note : DRAUP’s Talent Simulation Module . We have analysed ~2,000 tech companies and ~10,000 start-ups.

Location Deep Dive : US

1818

Europe: Mature AI talent pool is employed by start-ups focussed in Fintech & Health-tech industries; Tech giants have made landmark acquisitions from University labs from their Europe HQ’d centres

2. High intensity of AI talent across start-ups focused on Industry Specific applications: Fintech, Health-tech and retail industries

1. High acquisition focus: US tech giants have been leveraging mature AI talent from start-ups

1000+Industry specific start-ups

40%Fintech

20%Health Tech

10%Manufacturing

Bolster tech Stack

3. Build in Europe, move to US to scale : Key start-ups move research labs to US for raising late stage rounds and expand customer base

30+Ai start-ups have set-up US and UK based research labs

InfiDo- Bay Area

Founded by Oxford graduates; Raised Series C and set-up bay area lab to expand its US business

Feedzai - NewYork

Founded n Portugal; launched in US and then in UK in 2016

Google - DeepMind, Dark Blue labs

Amazon -Angel.AI

Acqui-hire

Microsoft -Swift KeyBuild New Products

Mature AI talent pool concentrated across Start-ups and Universities

Note : DRAUP’s Talent Simulation Module . We have analysed ~2,000 tech companies and ~10,000 start-ups.

Location Deep Dive : Europe

1919

Europe : Western Europe is the hotspot for AI & Big Data talent while Eastern Europe startup ecosystem is rapidly maturing

Supply Drivers

Talent Quality Talent Scalability# Cost Benefits

UK has high quality talent in big data

software and analytics

Low scalability due to small fresh university

talent supply

UK has among the highest talent cost for

the given talent quality

It is an emerging AI/Big data fresh

talent base

High scalability due to strong presence of young talent pool

Average talent cost as most of them are university talents

Has largest supply of AI/Big data talents after UK in Europe

High scalability due to high supply of fresh

university talents

High talent cost as the country is emerging to be an AI hub in Europe

Has limited supply of AI/Big data talents

Low scalability since AI/Big data based

courses are yet to rise

Low talent cost for the existing analytics/ ML

talent in the region

~ 120,000AI/Big Data Talent

Others

9%

UK

28%

72%Start-ups

Tech

Companies

32K+ Talent

27%

Germany

46%

54%Start-ups

Tech

Companies

31K+ Talent

27%

France

41%

59%Start-ups

Tech

Companies

23K+ Talent

19%

Eastern Europe

43%

67%Start-ups

Tech

Companies

21K+ Talent

18%

10K+ Talent

United Kingdom

Germany

France

Eastern Europe

Note : DRAUP’s Talent Simulation Module . We have analysed ~2,000 tech companies and ~10,000 start-ups.

Location Deep Dive : Europe

2020

UK: United Kingdom’s AI & Big Data talent is largely employed by platform start-ups while tech giants have built their engineering teams by acquihiring from start-ups and universities

United Kingdom

~ 32,000Demand talent

$150,000Median Cost

United Kingdom

18%

Data Engineer

34%

Data Manager

29%

Data Scientist

17%

Data Architect

Headcount Distribution

(By Skills)1%

Applied AI

Key Employers Total Employable Talent

AI/Big Data start-ups

G500 companies 9.2K+

~ 480

AI/Big Data Universities 16

Top Verticals

23K+Total Number

Information Technology and Services, Fintech, HR Tech

Tech companies Start-ups

Note : DRAUP’s Talent Simulation Module . We have analysed ~2,000 tech companies and ~10,000 start-ups.

Location Deep Dive : Europe

2121

UK : Tech giants employ majority of Data Science talent while Banking giants have large scale Data analyst teams working on digital transformation of front-end and back end operations

Data

Scientist

Database

Engineer

Applied

ML

Data

Architect

Analyst –

Data

Management

1000 63% 25% 1% 1% 10%

2500 21% 17% 0% 45%Lloyds has pledged to train 2.5m people, charities and small businesses in free digital skills by 2020 in a partnership with the UK government

1500 42% 8%Microsoft is using AI and Machine Learning to Discover a Cure for Cancer in it’s Cambridge UK Lab

500 21% 22% 0% 25% 32%

HSBC is planning to integrate the AI software of Quantexa, a UK-based start-up, to screen the vast amounts of data it holds on customers and their transactions against publicly available data, in the search for suspicious activity.

1000 30% 14% 48% 4%The Deepmind Applies Team is collaborating with clinicians in the UK’s National Health Service on delivering better care for conditions that affect millions of people worldwide.

AI & Big Data

Headcount

Top 5 tech companies AI & Big Data head count ~7000

Facebook has opened its new London office and said it will create 800 high-tech jobs in the UK over the next year

0.5% 16% 33.5%

17%

4%

Tech companies Start-ups

Note : DRAUP’s Talent Simulation Module . We have analysed ~2,000 tech companies and ~10,000 start-ups.

Location Deep Dive : Europe

2222

Start-Ups: Major employers are Fintech and Health-Tech startups and attract talent from large banking giants

Finance

NLP

Healthcare

Top Verticals/Tech focus

Key Start-ups Key Job profiles Previous Experience

Retail

Workloads/ Skills

• Design scalable, performance algorithms to provide better and more intelligent user experiences

Senior Data Scientist

• Modelling and verification of complex video processes in C++ and Python to support the development of the corresponding real-time digital logic.

Machine Leaning Scientist

• Implementing multiple high-performance algorithms making the most out of AWS GPU instances and deep-learning applications using Torch framework, Lua and C++

Lead Applied Researcher

• Data modelling, cleaning and summarization. Working with NLP (n-grams, POS tagging, TF-IDF, topic modelling, clustering) Sklearn.

Machine Leaning Engineer

Senior Data Scientist

• Analysis of new data streams for inclusion in our real-time ad targeting engine. Prototyping real-time machine learning algorithms using cutting edge research

• Working with Natural language processing, adversarial learning, reinforcement learning, active learning, probabilistic Bayesian learning,.

NLP Developer Engineer

• Monitoring using CloudWatch, Cacti, netdata. Cleaning, gathering, and merging data from a diverse set of sources and automating associated processes

DevOps Engineer

Data Scientist/ Machine Learning Engineer

• Development of deep learning, multi-agent, and expert systems products. Developing traffic prediction algorithms.

~480

Total Number of AI/Big Data Start-ups

~$80K

Median Salary

Total Start-Up Talent pool

Tech companies Start-ups

Note : DRAUP’s Talent Simulation Module . We have analysed ~2,000 tech companies and ~10,000 start-ups.

Location Deep Dive : Europe

2323

University Fresh graduates: India and China have high percentage of employable talent pool for AI & Big Data

~2.6 Mn

Big Data Analytics, Computer Vision, Natural

Language Processing, Machine Learning

Global Available Software Talent

14

0

4

0

4

0

4Total Employable Big

Data/ML Talent

300K – 320k23

Europe~96,000

USA~40,000

Canada

~18,000

China~80,000

India~37,000

Tier 1

~ 80KTier 2

~ 160KTier 3

~ 27K

Total AI professors –~1300 - 1400

Research Focus Areas – ML, Computer Vision

Top Employers in top universities – Uber, Amazon, Adobe, Google, Microsoft

Total AI professors –~150 -250

Research Focus Areas – ML, Computer Vision

Top Employers in top universities – Uber, Google, Citi

Total AI professors –~ 550 - 650

Research Focus Areas – Computer Vision, ML

Top Employers in top universities – Google Microsoft, Facebook

Total AI professors –~50 - 100

Research Focus Areas –ML

Top Employers in top universities – Amazon, Flipkart, Microsoft

Total AI professors –~450 - 550

Research Focus Areas –NLP, Computer Vision

Top Employers in top universities – Tencent, Baidu, Alibaba, Google, Microsoft, Huwaei

Note : DRAUP’s Talent Module analysed 100,000+ global universities to identify top universities and key courses in software engineering, ML and Big Data

32,000UK

24,000Germany

12,000France

5,000S. America

2,000Israel

6,000Singapore

8,000Africa

18,000Australia

Supply Analysis

2424

DRAUP Methodology : Top university ranking

No. of ML/BD courses

No. of ML/BDpublications

No. of Masters/Phds

CoE of techcompanies

Startups Born

Maturity of AL/MLcourses

University 1 University 2 University 3

University 4 University 5

1Maturity of ML/BD coursesMaturity of the courses has been calculated by analyzing depth of courses, number of enrollments, no. of citations of publication by professor teaching the course etc.

2No. of ML/BD coursesTotal number of ML and Big Data courses taught in the university

3No. of ML/BD publicationsNumber of ML and Big Data publications done by the professors/phds of the universities

4No. of Masters/Phds

5CoE of tech companies

6Start-ups born

1

2

3

4

5

6

Number of ML and Big Data publications done by the professors/phds of the universities

If tech companies have opened Centre of Excellence for AI or Big Data by tying up with the universities

Number of startups born from the universityNote : The ranking shown is a sample

Note : DRAUP’s Talent Module analysed 100,000+ global universities to identify top universities and key courses in software engineering, ML and Big Data