www.upxacademy.com

How to Crack Big Data & Data Science Roles

Peeyush Taori

London Business School, AQR, AQR Asset Management

Institute, Indian School of Business

Manvender Singh Founder, UpX Academy

MBA, Indian School of Business, Hyderabad

Agenda of Today’s Infosession

• Why is there buzz about Big Data, Machine Learning & Data Science • What is the future of Big Data & Data Science as a career? • Which companies are hiring for Big Data, Machine learning & Data

Science experts? • How to position yourself to crack these roles? • Interviews questions for Big Data & Data Science professionals • Info about upcoming batches • Q&A

A quick look at some people you will meet

Peeyush Taori Manvender Singh Madhu Reddy Arun Reddy Chief Instructor Founder Student Services Student Services

What this session is

• Insights that you’ll not get on internet • Focused on end goal(career opportunities) not starting

point(learning big data & data science) • Understand big data & data science career opportunities across

geographies & industries • Understand how to make career transition into Big data & Data

Science • Address your questions related to career opportunities in Big data &

Data Science

What this session is not

• Not an introductory session on Big Data & Data Science

• Attend Big Data and Data Science trial classes Big Data Trial class 12-1 pm Sunday 11th Sept Data Science Trial class 1-2 pm Sunday 11th Sept

The buzz

“The Sexiest job of the 21st century “ “#1 most wanted hires in USA in 2016” “Shortage of 140k to 190k data scientists in US alone by 2018” “We’re moving from a mobile first world to AI first world”

How does Big Data analytics affect our daily lives?

More use cases on : http://upxacademy.com/2016/05/31/big-data-use-cases-industries/

The buzz

“The Sexiest job of the 21st century “ “#1 most wanted hires in USA in 2016” “Shortage of 140k to 190k data scientists in US alone by 2018” “We’re moving from a mobile first world to AI first world”

Machine learning applications

Self driving cars: Google, Baidu, Tesla have implemented this technology.

Speech recognition: Google now, Siri, Cortana

Genetics: Clustering algorithms are used in genetics to help find genes associated with a particular disease.

Face recognition: Facebook automatically tags people in photos where they appear.

Major acquisitions of ML and Big Data start-ups

2016

Intel acquired AI startup Nervana Systems for $350 million

Twitter acquired machine learning startup Magic Pony Technology for $150 million

Apple acquired Machine-Learning Startup Turi for $200 Million

A non-profit AI research company, OpenAI is funded by the famous business magnate Elon Musk

2015

Microsoft acquired Metanautix, a Big Data Analytics company

Big Data & Data Science - Together

• Fundamentally, part of same team – Big Data programming and data science go hand in hand

• Firms need to deal with huge amounts of data – Storage, Computation, Coherent Data View – Big Data

– Analytics, Statistics, Prediction – Data Science

• Let’s consider them in isolation for now

Big Data…What and Why?

Characterized by 3V

• Volume

• Velocity

1. 3 Exabytes data(3 billion GB) is generated every day

2. 13 million new videos are added/month on Youtube.

3. 300 million photos uploaded/day on Facebook

• Variety

1. Structured, Semi-Structured, Unstructured

Data is the most valuable asset

• Create insights and value

General Batch Processing

Pregel

Dremel

Impala

GraphLab

Giraph

Drill Tez

S4

Storm

Specialized Systems

(iterative, interactive, ML, streaming, graph, SQL, etc)

General Unified Engine

(2004 – 2013) (2007 – 2015?) (2014 – ?)

Mahout

Technology Landscape

Career Paths

Big Data Developer

• Excel at Big Data programming

• Hadoop, Pig, Hive, HBase, Spark

• Big Data Engineer, Consultant, Big Data Architect

Big Data Analytics

• Wear data analytics and big data programming hats

• Hadoop, Spark, Statistics, Analytics, Data Science, R, Python

• Big Data Analyst, Consultant, Big Data scientist

Big Data Jobs trends

Now, let us consider Data Science

Data Science…What and Why?

Skills a recruiters seeks

Typical Workday of a Data Scientist

Gather data • Programming, web scraping, DB

Transform data • DB Skills, Data Manipulation, Mathematics & Stats

Data Modeling • Machine Learning, Stats, Algorithms

Data Reporting • Inference, Business Acumen, Visualization

Data Science Job Trends

Demand across geographies • Hottest market in US and Europe currently

• Demand outstrips supply

• Average salary of $1,00,000 for Big Data Engineers and $1,20,000 for Data Scientists

• Similarly, £60,000 in UK

• Fastest growing job sector in India

• Average starting salary- INR 10 Lakhs

• Salaries shoot up with skill set and experience

Who is recruiting? Basically, everyone!!!

Thought Leaders

• Google, Facebook, Amazon

Data driven firms • Uber, Twitter, NBC, Flipkart

IT giants

• Catching up to the buzz • Infosys, Cognizant, IBM, Accenture…..

Data analytics focused startups/companies

• Arcadia, DataHero, Walmart Labs, Mu sigma, Fractal Analytics, Flutura

Traditional Businesses • DNV, Wal-Mart, Sears, DHL

Building a Resume Typical CV attention time span ~ 20-30 sec

Prior Big Data/Data Science experience

• Most recent (Chronological)

• Project

• Clear, concise articulation of responsibilities and tools used

Keep other experience to a minimum

Demonstration of Big Data/Data Science Skills

• Certification

• Personal projects/POC/Competitions

Finally, KISS

• Keep It Simple and Short

No prior experience?

Demonstration of certified skills takes top priority

Experience of working on Big Data/Data Science projects

Experience of distributed computing

Knowledge of fringe skills

Intra-organization

• Low barriers to movement

• Certification and POC puts you in spotlight

What not to put in resume

• Recruiters receive lot of CVs

• Formatting and presentation matters

• Many firms use keyword extractor tool

• Buzzwords without knowledge is a strict no-no

• Keep length to max 2 pages

Big Data Top interview questions - Generic

• Explain Big Data technologies

• Walk us through your previous Big Data project

• What is Hadoop and how is it related to MapReduce

• Hadoop deamons & their roles in Hadoop cluster

• Explain MapReduce

• Difference between Spark and Hadoop

• How do I deal with Streaming data

• Hive, Pig, and MapReduce

Big Data Top Interview Questions - Specific

• Difference between Hadoop 1.0 and 2.0

• Architecture of Spark

• Indexing process in HDFS

• HDFS Block and Input Split

Data Science Top interview questions - Generic

• Explain various Machine Learning techniques

• Walk us through your recent data science project

• Difference between supervised and unsupervised

• Assumption for a linear regression

• How do random forests work

• Trade-off between classification and regression

Data Science Top Interview Questions - Specific

• How do you handle missing data

• Differentiate: Lift, KPI, model fitting

• Collaborative filtering, n-grams, KNN

• Assumptions of LDA and QDA

Class FAQs

• Where do the classes take place & what’s the class timings? • Can I attend trial classes before attending? • Do I have to purchase any software?

• What’s the difference between certificate of completion vs certification?

• What if I miss a class?

• How do I ask my doubts after the class?

Payment FAQs

• 20% off on course fee after trial classes. Valid till tomorrow midnight. Use UPX20 coupon code

• One time payment on website

• Credit card EMI option- currently available for ICICI, HDFC, Kotak & Amex

• 3 month interest free EMI option for select corporates.

Coordinates

Manav manav@upxacademy.com Peeyush peeyush@upxacademy.com Student Service Team: info@upxacademy.com 1800-123-1260 Fasahath/Madhu : 733-736-0431/37

Q&A