Data Scientist – ML

📋 Description

• Oversee the design, development, and implementation of scalable machine learning solutions aimed at pricing optimization, demand forecasting, and promotion planning.

• Construct and enhance statistical and machine learning models for:

• - Demand forecasting

• - Price elasticity modeling

• - Promotion optimization

• - Inventory and revenue forecasting

• Create, build, and deploy robust ML pipelines within Databricks, and establish model monitoring systems along with production-ready APIs.

• Possess the capability to design and assess transformer-based time series forecasting models for extensive retail sales forecasting and demand planning.

• Encourage experimentation, model assessment, and ongoing enhancement of forecasting and pricing models.

• Analyze extensive structured and unstructured retail datasets to reveal trends, customer behavior patterns, and pricing insights.

• Formulate data-driven strategies that enhance revenue, profitability, and pricing efficiency across various products and categories.

• Utilize advanced statistical methodologies and machine learning algorithms to address complex retail business challenges.

• Collaborate closely with Product, Engineering, Data Engineering, and Business teams to translate business requirements into scalable ML solutions.

• Mentor junior data scientists and provide technical support across cross-functional teams.

• Clearly communicate analytical findings and business recommendations to both technical and non-technical stakeholders.

⛳️ Requirements

• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related discipline.

• Over 5 years of practical experience in Machine Learning and Data Science.

• Strong foundation in mathematics, probability, statistics, and regression analysis.

• Comprehensive understanding of traditional machine learning algorithms and statistical modeling techniques.

• Proficient programming skills in Python, including:

• - Pandas

• - NumPy

• - Object-Oriented Programming (OOP)

• - Scikit-learn

• - TensorFlow or similar ML frameworks

• Experience working with PySpark and large-scale data processing systems.

• Strong SQL skills with experience in relational databases and data warehouses.

• Experience in developing APIs and ML services utilizing Flask or similar frameworks.

• Over 5 years of experience in Retail, CPG, or E-Commerce sectors with expertise in:

• - Demand forecasting

• - Price elasticity

• - Promotion optimization

• - Pricing strategy

• Familiarity with MLOps platforms and deployment pipelines such as:

• - Databricks

• - Large Language Models (LLMs)

• - Google Vertex AI

• - Amazon SageMaker

• - Azure Machine Learning

• Experience in building and maintaining CI/CD pipelines for ML workflows.

🏝️ Benefits

• Opportunities for professional development.