Job Summary:
As a part of the data science team of C5i, we are looking for an experienced and strategic Senior Data Scientist to join our high-impact analytics team in the.
This position will require you to work on the development of Resource Allocation Model that directly influences how we allocate marketing & media budgets, drive consumer demand, and enhance companys performance.
This is a hands-on technical role requiring deep expertise in data science, machine learning, and business acumen to solve complex problems in a fast-paced, consumer-centric environment.
Job Responsibilities:
- Develop, validate, and scale Resource Allocation Model to quantify the impact of Sales & Marketing packages on sales and brand performance.
- Implement optimization algorithms to inform budget allocation and maximize marketing ROI across geographies and product portfolios.
- Lead the development of predictive and prescriptive models to support commercial, trade, and brand teams.
- Leverage PySpark to manage and transform large-scale retail, media, and consumer datasets.
- Build and deploy ML models using Python and TensorFlow, ensuring robust model performance and business relevance.
- Collaborate with marketing, category, and commercial stakeholders to embed insights into strategic decisions.
- Use GitHub Actions for version control, CI/CD workflows, DVC for data versioning, and reproducible ML pipelines.
- Present findings through compelling data storytelling and dashboards for senior leadership.
- Mentor junior data scientists and contribute to a culture of innovation and excellence.
Requirements & Qualifications:
- 5+ years of hands-on experience in data science, preferably within the FMCG or retail domain.
- Proven track record of building and deploying Marketing Mix Models and/or media attribution models.
- Deep knowledge of optimization techniques (e.g., linear programming, genetic algorithms, constrained optimization).
- Advanced programming skills in Python (pandas, scikit-learn, statsmodels, TensorFlow).
- Expertise in PySpark for distributed data processing and transformation.
- Experience with Git and GitHub Actions for collaborative development and CI/CD pipelines.
- Strong grounding in statistics, experimental design (A/B testing), and causal inference
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