OR Jobs in
India
● Career Options
● Companies
● Hiring Process
Alok Patel
Email id: or.ai.alok@gmail.com
1
Career options for OR Graduates
Data Science
OR scientist/Analyst
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Data Scientist
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Data Engineer
Operations Research
Modeling, Coding, Algorithms, Solution techniques
OR Consultant
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Domain expertise
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Modeling tools - Supply chain guru, JDA, o9
Simulation Engineer
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DES, Monte-carlo, ABM; Anylogic, Arena, SIMUL8
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OR scientist/analyst/engineer
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OR Consultant
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Data analysis, visualization; SQL, Power BI, Tableau
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Simulation Engineer
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Business acumen
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Supply chain analyst
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forecasting/planning/capacity planner
Business analyst
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Operations
Analyst
Common skills:
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Communication
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Problem solving
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Leadership/Initiative/Ownership
2
Companies Hiring OR Graduates in India
Consultancy:
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BCG, McKinsey, Bain & Co, TCS, Wipro, Infosys,...
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Big 4 - EY, PWC, KPMG, Deloitte
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ITC Infotech, FICO
Retail
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Amazon, Flipkart, Target, Walmart, Udaan, Reliance
Product
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Dell, Apple, Intel, Micron, Bayer
Start-ups
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Optym, JDA, o9, Coupa, Ormae
R&D:
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Mercedes, Ford, TCS Innovation labs,
Microsoft, IBM
Airlines:
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Indigo, Air Asia, United Airlines, Emirates
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Manufacturing - Boeing, Airbus - Design and supply
chain optimization roles
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Consulting - Sabre, Laminaar, Amadeus
FMCG:
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Unilever, ITC, Mondelēz
Logistics:
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DHL, Delhivery, Ecom
many more...
3
Hiring Process - Evaluation Sheet
Skills required for freshers: Relevant coursework,
Coding, Modeling, Solution techniques, Collaboration
and Communication
4
Job
Preparation
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Planning
Resume
Technical
Behavioural
Alok Patel
Email id: or.ai.alok@gmail.com
5
Make your own timeline
Fix job role of your interest & skills
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Make a list of companies
Analyse job ads
Start networking
09.05.XX
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09.17.XX
List out the gaps
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Give practice interviews
Start working to fill gaps
Skills
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Technical
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Behavioral
Projects
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Hands-on experience
Do online courses
Read books, blogs and articles
Do hands on and make a project portfolio
10.13.XX
10.20.XX
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Invite alumni
Role play among
classmates
11.01.XX
Resume making
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Customize for each company and
job role
Spend significant time to ensure
good quality resume
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Resume guidelines
Read this book
Must read chapters
Cracking the PM Interview: How to Land a Product
Manager Job in Technology by Gayle Laakmann
McDowell and Jackie Bavaro
Ch 7 - Resumes
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The 15 Second Rule
The Rules
Attributes of a Good PM Resume
What to Include
Ch 8 - Real Resumes: Before & After
Ch 11 - Define Yourself
Ch 12 - Behavioural questions
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Check your resume score (https://resumeworded.com/)
Use feedbacks to improve the score (higher the better)
Harvard resume guidelines (link)
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Preparation - OR Scientist/Analyst (Freshers)
Optimization Coursework:
1.
OR - 1: Models and Applications
2.
OR - 2: Optimization Algorithms
3.
OR - 3: Theory
4.
Discrete Optimization (advanced)
5.
Metaheuristics
Coding:
1.
2.
3.
2022 Complete Python Bootcamp From Zero to
Hero in Python
Optimization with Python: Solve Operations
Research Problems
SQL for Data Science
DSA:
1.
Mathematical modeling:
1.
H. Paul Williams
2.
Advanced modeling: blog
Hands-on Projects:
1.
VRP-REP
2.
Gurobi examples (Gurobi quick start guide); or-tools
Books:
1.
Applied Mathematical Programming. by Bradley, Hax,
and Magnanti
2.
Data Structures and Algorithms Specialization
Book: Model Building in Mathematical Programming by
Network Flows: Theory, Algorithms, and Applications by
Ravindra Ahuja, Thomas Magnanti, James Orlin
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Behavioral/HR Interview Preparation
6 Types of stories you should have on hand for job interviews
(link)
1.
2.
3.
4.
5.
6.
When You Solved a Problem
When You Overcame a Challenge
When You Made a Mistake
When You Worked as a Leader
When You Worked With a Team
When You Did Something Interesting
30 Behavioral Interview Questions you should be ready to
answer (link)
Must have good answers to these questions:
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Tell us about yourself?
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Why do you want to work with us?
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Why should we hire you?
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What do you like to do in your spare time?
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Where do you want to see yourself in next 3/5 years?
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What are your strengths and weaknesses?
STAR Interview Method: Link
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Additional Resources
for Technical
Interviews
● Theory syllabus
● Resource Links
Alok Patel
Email id: or.ai.alok@gmail.com
10
Technical Interview Preparation - OR Scientist/Analyst
Optimization concepts:
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LP: Simplex, shadow price, reduced cost, Dual
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Logical constraints
and strong), complementary slackness, sensitivity
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Big-M constraints
analysis, barrier algorithms
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Absolute value function
MIP: branch & bound, branch & cut, branch &
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Min/Max
price, decomposition techniques, column
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Cut generation
generation
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Sub-tour elimination
NLP: KKT conditions, gradient descent algorithms,
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SOS type 1 & 2
Lagrangian relaxation
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Linearization
simplex, primal - dual conversion, duality (weak
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Mathematical modeling:
Network flow models and algorithms
Software development:
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Data Structures, Algorithms, Complexity
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Software development life cycle (link)
Practice as many problems as you can from this book.
Model Building in Mathematical Programming by H. Paul
Williams
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Technical Interview Preparation - OR Scientist/Analyst
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Learn some metaheuristics - genetic algorithm, particle
swarm optimization, tabu search, etc.. Implement some of
them to solve a real-world problem.
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object-oriented programming.
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Metaheuristic Optimization: Link
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Efficient coding using Python: Link
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Python + Pulp + CBC/Cplex/Gurobi: Link
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Mathematical Optimization: Solving Problems
Learn how to do efficient coding using python or any other
language. Do some hands on coding involving
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Resources:
using SCIP and Python: Link
Learn one of these, Python + Pulp (CBC/GLPK), Python + MIP,
Python + SCIP, Pyomo, Jump, GurobiPy.
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Python + MIP: Link
Learn google OR tools to solve routing and scheduling
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Google OR Tools: Link
problems.
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Gurobi blogs: Link
Implement decomposition, column generation or search
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OR Stack exchange: Link
heuristics to solve large scale optimization problems.
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Yet Another Math Programming Consultant: Link
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Informs case studies: Link
Learn to read optimization solvers logs and parameter
tunings
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