Data Scientist

If solving business challenges drives you. This is the place to be. Fornax is a team of cross-functional individuals who solve critical business challenges using core concepts of analytics, critical thinking.

We are seeking a skilled Data Scientist who has worked in the Marketing domain. The ideal candidate will possess a strong blend of statistical expertise and business acumen, particularly in Marketing Mix Modeling (MMM), Causality Analysis, and Marketing Incrementality. Good understanding of the entire marketing value chain and measurement strategies.

The Data Scientist will play a critical role in developing advanced analytical solutions to measure marketing effectiveness, optimize marketing spend, and drive data-driven decision making. This role involves working closely with marketing teams, analysts, and business stakeholders to deliver actionable insights through statistical modeling and experimentation. The ideal candidate has a strong background in statistical analysis, causal inference, and marketing analytics.

Responsibilities :

Modeling & Analysis (70%)

• Develop and maintain Marketing Mix Models (MMM) to measure the effectiveness of marketing channels and campaigns
• Design and implement causal inference methodologies to identify true incremental impact of marketing activities
• Build attribution models to understand customer journey and touchpoint effectiveness
• Conduct advanced statistical analysis including regression, time series, and Bayesian methods
• Develop predictive models for customer behavior, campaign performance, and ROI optimization
• Create experimental designs for A/B testing and incrementality studies
• Perform promotional analysis to measure lift, cannibalization, and optimal discount strategies across products and channels

Stakeholder Management & Collaboration ( 30% )

• Partner with business teams to understand business objectives and analytical needs
• Translate complex statistical findings into actionable business recommendations
• Present analytical insights and model results to non-technical stakeholders
• Collaborate with data engineers to ensure data quality and availability for modeling
• Work with business teams to design and implement measurement strategies
• Create documentation and knowledge transfer materials for analytical methodologies

Key Qualifications

Education:

Experience:

Technical Skills:

• Strong proficiency in Python or R for statistical analysis
• Expertise in statistical modeling techniques (regression, time series, Bayesian methods)
• Experience with Marketing Mix Modeling (MMM) frameworks and tools
• Knowledge of causal inference methods (DiD, IV, RDD, Synthetic Controls)
• Proficiency in SQL for data manipulation and analysis
• Understanding of machine learning algorithms and their applications
• Deep understanding of marketing channels and measurement strategies
• Familiarity with marketing metrics (CAC, LTV, ROAS, etc.)
• Understanding of media planning and optimization concepts