Decision Scientist

Capgemini

Decision Scientist measuring media effectiveness for a major insurance and financial services group. Designing incrementality tests, causal analyses, and marketing measurement models to optimize media investments.

Posted 8/15/2026full-timeRemote • 🇲🇽 MexicoMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in Analytics and Data Science, with a strong focus on incrementality testing, causal inference tools, and the ability to communicate actionable insights to diverse stakeholders. Proficient in handling large datasets and utilizing programming languages and tools to enhance marketing measurement and effectiveness.

Highest-signal resume keywords

Incrementality TestingCausal Inference ToolsR or Python ProgrammingSQLPowerBI

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

AnalyticsData ScienceExperimental DesignMarketing MeasurementData Analysis

Soft Skills

CommunicationCollaborationStakeholder Engagement

Industry Keywords

Marketing EffectivenessMedia InvestmentsCausal InferenceDifference-in-DifferencesSynthetic ControlsPropensity Score Matching

Tech Stack

Tools & technologies

PythonSQL

About the role

Key responsibilities & impact

Plan and implement incrementality tests
Analyze output of MMM models
Develop other forms of marketing measurement to provide a full picture of marketing effectiveness
Communicate results to leadership and stakeholders
Partner with cross-functional stakeholders to deliver actionable insights that optimize media investments and improve business outcomes
Interpret analytical results for stakeholders ranging from entry-level employees to C-suite leaders
Provide clear, actionable insights to improve marketing efficiency

Requirements

What you’ll need

At least 3 years of experience in Analytics and/or Data Science
Bachelor’s degree in a technical field
Fluency in English
Experience working with large and complex datasets
Experience applying causal inference tools, including Difference-in-Differences, synthetic controls, and propensity score matching, to real-life problems
Experience with experimental design and incrementality testing
Working knowledge of R or Python, SQL, and PowerBI
Valid, local legal authorization to work in the country where the role is based at the time of hire
FBS does not sponsor or obtain work authorization unless explicitly stated

Benefits

Comp & perks

Competitive salary and performance-based bonuses
Comprehensive benefits package
Career development and training opportunities
Flexible work arrangements (remote)
Dynamic and inclusive work culture within a globally renowned group
Private Health and Dental Insurance
Pension Plan
Meals tickets
Life Insurance