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Job Description – Lead Data Scientist / Data Analyst – Retail Analytics- Bengaluru

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Job Description – Lead Data Scientist / Data Analyst – Retail AnalyticsAbout Mantle Solutions:

As a Lead Data Scientist / Data Analyst, you'll combine analytical thinking, business acumen, and technical expertise to design and deliver impactful data-driven solutions. You'll lead analytical problem-solving for retail clients — from data exploration and visualization to predictive modeling and actionable business insights.

Key Responsibilities

  • Partner with business stakeholders to understand problems and translate them into analytical solutions.
  • Lead end-to-end analytics projects — from hypothesis framing and data wrangling to insight delivery and model implementation.
  • Drive exploratory data analysis (EDA), identify patterns/trends, and derive meaningful business stories from data.
  • Design and implement statistical and machine learning models (e.g., segmentation, propensity, CLTV, price/promo optimization).
  • Build and automate dashboards, KPI frameworks, and reports for ongoing business monitoring.
  • Collaborate with data engineering and product teams to deploy solutions in production environments.
  • Present complex analyses in a clear, business-oriented way, influencing decision-making across retail categories.
  • Promote an agile, experiment-driven approach to analytics delivery.

Common Use Cases You'll Work On

  • Customer segmentation (RFM, mission-based, behavioral)
  • Price and promo effectiveness
  • Assortment and space optimization
  • CLTV and churn prediction
  • Store performance analytics and benchmarking
  • Campaign measurement and targeting
  • Category in-depth reviews and presentation to L1 leadership team

Required Skills and Experience

  • 3+ years of experience in data science, analytics, or consulting (preferably in the retail domain)
  • Proven ability to connect business questions to analytical solutions and communicate insights effectively
  • Strong SQL skills for data manipulation and querying large datasets
  • Advanced Python for statistical analysis, machine learning, and data processing
  • Intermediate PySpark / Databricks skills for working with big data
  • Comfortable with data visualization tools (Power BI, Tableau, or similar)
  • Knowledge of statistical techniques (Hypothesis testing, ANOVA, regression, A/B testing, etc.)
  • Familiarity with agile project management tools (JIRA, Trello, etc.)

Good to Have

  • Experience designing data pipelines or analytical workflows in cloud environments (Azure preferred)
  • Strong understanding of retail KPIs (sales, margin, penetration, conversion, ATV, UPT, etc.)
  • Prior exposure to Promotion or Pricing analytics
  • Dashboard development or reporting automation expertise

Job Type: Full-time

Pay: ₹800,000.00 - ₹900,000.00 per year

Work Location: In person

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