Data Science Professional

Celebal Technologies; Mumbai; On-site; INR 900,000 - 1,500,000; Full time

Job summary

Celebal Technologies in Mumbai invites applications for an analytics role. You will translate business problems into analytical approaches, perform advanced analyses, and deliver actionable insights to improve KPIs across divisions.

You will collaborate with Product, Tech, and Marketing to implement analytics-driven interventions and work with Data Engineering to ensure data readiness and pipeline support. Experience with ML/AI techniques and BI tools will be valued, helping build reusable

Qualifications

• B.Tech/BCA or Graduation.
• Strong SQL, Python/R, and statistical modelling skills.
• Translate business context into analytical problems.
• Expertise relevant to the track (e.g., Customer Intelligence, Marketing Sciences, Pricing, Product Analytics).
• Knowledge of ML/AI techniques: regression, classification, segmentation, causal inference, uplift modelling, MMM, forecasting, NLP, embeddings.
• Experience with BI/visualization tools (Tableau, PowerBI) for insights and storytelling.
• Understanding large-scale data environments, data hygiene, and measurement design.

Responsibilities

• Translate ambiguous business problems into structured analytical approaches.
• Conduct exploratory analysis, driver analyses, funnel analyses, segmentation, forecasting, and hypothesis testing.
• Build clear, actionable insights that drive revenue, reduce cost, or improve customer and operational KPIs.
• Partner with Product, Tech, Category, Supply Chain, Marketing and Finance teams to understand pain points and define analytics-driven interventions.
• Work closely with Data Engineering teams on data readiness and pipeline requirements.
• Apply advanced ML/AI methods such as embeddings, causal inference, MMM, recommendation insights, anomaly detection, driver trees.

Skills

SQL

Python

Statistical modelling

Education

B.Tech/BCA or Graduation

Tools

Tableau

PowerBI

Job description

Skills

• SQL
• Python
• statistical modelling skills

Problem Solving & Insights

1. Translate ambiguous business problems into structured analytical approaches.
2. Conduct exploratory analysis, driver analyses, funnel analyses, segmentation, forecasting, and hypothesis testing.
3. Build clear, actionable insights that drive revenue, reduce cost, or improve customer and operational KPIs.

Model Development & Decision Frameworks

1. Build predictive, prescriptive and causal models (e.g., churn, CLTV, attribution, price elasticity, anomaly detection, uplift modelling).
2. Develop measurement frameworks, scorecards, and reusable decision-support tools for divisions.

Reusable Asset & Framework Creation

1. Build modular, scalable assets that can be adopted by multiple divisions with minimal customization.
2. Standardize logic, definitions, taxonomies and measurement approaches within the expertise area.

Deployment & Adoption

1. Work with divisional analytics teams (hub & spoke model) to ensure adoption of frameworks, insights and models.
2. Support one division deeply while enabling self-serve adoption for others, as per CoE operating model.

Collaboration

1. Partner with Product, Tech, Category, Supply Chain, Marketing and Finance teams to understand pain points and define analytics-driven interventions.
2. Work closely with Data Engineering teams on data readiness and pipeline requirements.

Innovation & Experiments

1. Apply advanced ML/AI methods such as embeddings, causal inference, MMM, recommendation insights, anomaly detection, driver trees.
2. Support controlled experiments (A/B testing) and design best practice experiment frameworks.

Qualifications

• B.Tech/BCA or any Graduation
• Strong SQL, Python/R, and statistical modelling skills.
• Ability to translate business context into analytical problems.
• Expertise relevant to the specific track (e.g., Customer Intelligence, Marketing Sciences, Pricing, Product Analytics, etc.).
• Knowledge of ML/AI techniques: regression, classification, segmentation, causal inference, uplift modelling, MMM, forecasting, NLP, embeddings.
• Experience with BI/visualization tools (Tableau, PowerBI) for insights and storytelling.
• Understanding large-scale data environments, data hygiene, and measurement design.

Work Mode

Work from Office