Senior Data Scientist

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 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 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.