Data Scientist

Foom is a fast-growing company focused on retail, e-commerce, and consumer analytics, leveraging data-driven strategies to optimize business performance. We are looking for a Data Scientist who can help turn complex datasets into actionable insights, optimize models for forecasting and personalization, and support business decisions with data-backed strategies.

Job Description

1. Data Analysis & Insights

• Analyze sell-in, sell-out, stock availability, and transaction data from multiple sources (Odoo, PostgreSQL, Field Officer Apps, flagship store APIs, Customers).
• Build dashboards and reports to track key business metrics like sales performance, customer segmentation, and product trends.
• Conduct exploratory data analysis (EDA) to identify patterns and insights that drive business growth.
• Collaborate with marketing, finance, and operations teams to support decision-making with data-driven insights.

2. Predictive Analytics & Forecasting

• Develop predictive models for demand forecasting, pricing optimization, and inventory planning.
• Use time series forecasting to analyze sales trends and mitigate fluctuations due to promotions or seasonality.
• Implement customer behavior models to understand purchasing patterns and recommend targeted marketing strategies.

3. Data Cleansing, Normalization & Transformation

• Perform data cleansing, standardization, and normalization to improve data quality and consistency.
• Work with structured and unstructured data, handling missing values, duplicates, and outliers.
• Optimize data processing pipelines for scalability and efficiency.

4. Machine Learning & AI Implementation

• Develop and deploy machine learning models for customer segmentation, churn prediction, and recommendation systems.
• Implement clustering, classification, regression, and NLP techniques to extract meaningful insights.
• Optimize models for real-time decision-making in pricing, promotions, and customer targeting.

5. Data Engineering & Automation

• Design and maintain ETL pipelines to ingest, process, and store data efficiently.
• Automate data workflows and integrate external data sources (APIs, third-party data, and cloud databases).
• Collaborate with Data Engineers to optimize query performance and data warehouse architecture.

6. A/B Testing & Experimentation

• Design and execute A/B tests to evaluate marketing campaigns, pricing strategies, and product placements.
• Analyze customer behavior and conversion metrics to optimize user experience.
• Provide statistical validation of business hypotheses and guide decision-making based on test results.

General Qualification

Minimum Requirement

• Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.
• 3+ years of experience in data science, analytics, or machine learning.
• Proficiency in Python, R, or SQL for data analysis and model development.
• Experience with data visualization tools (Tableau, Metabase, Power BI, or similar).
• Strong knowledge of machine learning algorithms (classification, clustering, regression, deep learning).
• Experience working with large datasets and databases (PostgreSQL, MySQL, MongoDB, Google BigQuery, Snowflake).
• Familiarity with cloud platforms (AWS, GCP, or Azure) for data storage and computing.
• Strong problem-solving skills and business acumen to translate data into actionable insights.

Preferred Qualifications:

• Experience in retail, FMCG, or e-commerce analytics.
• Knowledge of marketing analytics, customer segmentation, and campaign performance analysis.
• Familiarity with big data frameworks (Spark, Hadoop, Airflow).
• Understanding of natural language processing (NLP) for sentiment analysis and customer feedback interpretation.
• Hands-on experience with A/B testing and causal inference methods.