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