Data Scientist

Location: Bengaluru

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, Num Py, 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/Mar Tech 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.