Senior Data Scientist

2 weeks ago

Bengaluru, Karnataka, India C5i Full time ₹ 15,00,000 - ₹ 25,00,000 per year

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.

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