Parcours Données et décision : Analyse et données

Objectives related to the intervention's introduction

• Get to know the world of Data Science Consulting
• Get to exchange on the different roles that exist in Data Science, in Consulting, the career paths
• Have a better understanding of Ekimetrics positioning, daily life, career paths…
• Open discussion on the different opportunities offered by companies (startups, big groups, big consulting, specialized) for Data Science career
• Get to know each other and discuss on the questions you might have

Objectives related to the course

• Recognize the importance and need for Operations Research / Mathematical Modelling and Optimization
• Formulate decision-marking problems from different industries (logistics, energy, classical operations-research problems…) as mathematical programs
• Be able to recognize the type of problem at hand: deterministic or with uncertainty ; linear, integer or non-linear?
• Be able to analyze, formalize and solve linear, integer, non linear problems along with problems of optimization under uncertainty
• Become familiar and know fundamentals about the Python-based open-source optimization modelling library Pyomo along with several state-of-the-art open-source solvers compatible with it (GLPK, IPOPT)

Objectives related to the Product Management Module

• Understand how critical / popular is becoming the product approach, and why
• Differenciate product from project approach
• Be aware of the main roles for building a Data Science product
• Understand the scope of Product Manager / Owner roles
• Understand the 3 phases for a successful product
• Double diamond diagram for building the Product Vision
• Be aware of some of the many tools that exist for the Discovery and Delivery phases, and have experimented with them in the workshops

Objectives related to the case study

• Discover what Data Science consulting can be through a case study based on a real client mission
• Learn how to present like a pro and defend your vision in front of a panel of managers and consultants acting as the client
• Go through some of the main phases of a Data Science strategy mission in an accelerated way
• See how data science consulting can help business improve its sustainability performance

Objectives related to the MMO (Marketing Mix & Optimization) Module

Part 1 - Introduction to MMO

• Understand what MMO is used for (questions it can answer, to whom it can benefits…) and why it’s a pertinent addition to the topics you know about in the Data Science world
• Have a basic understanding of the main outputs of MMO (ROIs, optimized budgets, classical graphs like layer curves…)
• Understand the basics on how the MMO works (regressions in this course). Reading again your course on statistics on the topic can be useful for basic elements (R2, p-value, correlation…)
• Understand how transformations can be applied while building models to replicate the business characteristics of specific levers (lag, adstock, diminishing return…)

Part 2 – Introduction to Media

• Have a basic understanding of the media ecosystem
• Be aware of the main media levers, associated key metrics, and main characteristics of each lever

Part 3 – Demonstration on OneVision Ekimetrics MMO Solution

• The demonstration is provided to better visualize how modelling can be done, along with the classic outputs that can be provided to Marketing teams for instance

Objectives related to the Data Science useful tools and technologies module

Part 1 - Introduction to MLOps (Optional)

• Be aware of the growing need of ML Engineers for the next few years
• Become familiar with MLOps, the role of ML Engineer and the key concepts behind MLOps

Part 2 - Cloud certifications & trainings

• Reminder on how important (and a differenciator) knowledge of Cloud for Data Science can be
• Guidelines on how and what trainings to choose for quickly gaining confidence on Cloud for Data Science for your next job

Part 3 - Useful tools & libraries

• Open discussion on very useful tools & libraries for Data Science
• Absolutely not exhaustive. The objective is to discuss together and ideate on this list

Course content

An introduction to the intervention (several modules) is provided with a brief presentation of Ekimetrics, Data Science consultancy group. Glimpses of what the daily life (and missions) of a data science consultants can be are revealed along with a first discussion on the different career opportunities in Data.

Then, the course provides a practical introduction to Mathematical Modelling and Optimization. Through this course, the students will learn how to model business problems as mathematical problems and solve them using the open-source library Pyomo, along with state-of-the-art solvers such as GLPK or IPOPT.

This course follows a pragmatic approach mixing theory and practice to ensure the students understand the fundamentals of optimization to the students in a short amount of time.

A short evaluation is made on the course.

A module dedicated to Marketing Mix Optimization will follow, along with a module introducing the use of Cloud for Data profiles, giving advices on trainings to follow to have a more attractive profile, including also an open discussion with some recommended additional tools usually not covered in school but which are very good differentiators while looking for a job.

Eventually, a case based on real Ekimetrics mission is introduced to the students, who are put into the shoes of Data Science strategy consultants who have 1 month to pitch their diagnosis and recommendation to the client, represented by experts, consultants and managers from Ekimetrics.