Job Title

Job Summary: As a part of the data science team of C5i, we are looking for an experienced and strategicSenior Data Scientistto join our high-impact analytics team in the. This position will require you to work on the development ofResource Allocation Modelthat directly influences how we allocate marketing & media budgets, drive consumer demand, and enhance company’s 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 scaleResource Allocation Modelto quantify the impact of Sales & Marketing packages on sales and brand performance. Implementoptimization algorithmsto 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. LeveragePySparkto manage and transform large-scale retail, media, and consumer datasets. Build and deploy ML models usingPythonandTensorFlow , ensuring robust model performance and business relevance. Collaborate with marketing, category, and commercial stakeholders to embed insights into strategic decisions. UseGitHub Actionsfor 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+ yearsof hands-on experience in data science, preferably within theFMCGor retail domain. Proven track record of building and deployingMarketing Mix Modelsand/or media attribution models. Deep knowledge ofoptimization techniques(e.g., linear programming, genetic algorithms, constrained optimization). Advanced programming skills inPython(pandas, scikit-learn, statsmodels, TensorFlow). Expertise inPySparkfor distributed data processing and transformation. Experience withGitandGitHub Actionsfor collaborative development and CI/CD pipelines. Strong grounding in statistics, experimental design (A/B testing), and causal inference.