Data Scientist

Job Title:

Data Scientist – Retail / Loyalty / CRM Analytics Experience:

3–5 Years Location:

India (Pune/Bangalore/Chennai/Gurugram) Employment Type:

Full-time

About the Role We are looking for a

Data Scientist with strong experience in Retail, Loyalty, or CRM analytics

to drive customer growth and marketing effectiveness through data-driven insights and predictive models. The ideal candidate is comfortable working with large customer datasets (transactions, loyalty activity, digital behavior, campaign touchpoints) and can translate business problems into

production-ready analytics and ML solutions . You will partner with business and engineering teams to build models and measurement frameworks that improve

acquisition, retention, engagement, personalization, and customer lifetime value .

Key Responsibilities • Develop predictive models for

churn, propensity (buy/upsell), next-best-action, CLV/LTV , and customer segmentation. • Build and validate

customer cohorts , loyalty performance tracking, and campaign effectiveness analytics. • Design

uplift / incremental impact

approaches where applicable (attribution model, test/control, A/B testing, causal methods). • Create features from multi-source customer data: POS/e-commerce transactions, loyalty events, web/app behavior, CRM interactions. • Collaborate with data engineering to operationalize models in scalable pipelines (batch/near real-time as needed). • Communicate insights and recommendations clearly to stakeholders (marketing, CRM, product, and leadership). • Ensure analytics solutions follow best practices around

data quality, governance, and privacy

(PII handling).

Required Skills & Qualifications • 3–5 years of professional experience as a Data Scientist in

Retail / Loyalty / CRM / Customer Analytics

domains. • Strong proficiency in

Python

(pandas, NumPy, scikit-learn) and

SQL . • Hands-on experience with supervised ML (classification/regression), segmentation/clustering, and model evaluation. • Strong understanding of customer/marketing metrics:

retention, churn, repeat rate, RFM, CAC, conversion, AOV, basket analysis, LTV . • Experience with experimentation concepts:

A/B testing, holdouts, bias checks, measurement discipline . • Ability to translate business problems into well-scoped analytical approaches and deliverables. • Strong communication skills with ability to explain methods, assumptions, and trade-offs to non-technical audiences.

Good to Have (Bonus) •

GenAI / LLM experience : text analytics on customer feedback, summarization, classification, embeddings, retrieval (RAG) for CRM insights. • Experience with big data tools:

Spark / Databricks , cloud platforms (Azure/AWS/GCP), and MLOps basics. • Familiarity with CRM/MarTech ecosystems (e.g., CDPs, marketing automation tools) and campaign orchestration concepts. • Recommender systems exposure (ranking, personalization, similarity models). • Knowledge of privacy/security practices related to customer data (masking, access controls, GDPR-like principles).

What We’re Looking For • Strong customer-growth mindset: ability to connect analytics work to real business outcomes. • High ownership: can take problems from ambiguity → analysis/model → recommendation → deployment-ready output. • Practical modeling approach: balances rigor with speed, clarity, and stakeholder usability. • Collaborative working style with strong documentation and repeatable workflows.