Job Description

Overview

We are seeking a highly motivated and skilled Data Scientist to join our team in the retail industry. The ideal candidate has at least 2 years of experience in data science, with expertise in data analysis, predictive modeling, and machine learning. Exposure to MLOps, feature engineering, and data engineering workflows will be considered a plus.

Responsibilities

Data Analysis: Collect, preprocess, and analyze large datasets to identify trends and actionable insights for retail business challenges.
Model Development: Design, train, and deploy machine learning models for tasks such as demand forecasting, customer behavior analysis, and inventory optimization.
Collaboration: Partner with cross-functional teams, including data engineers and business stakeholders, to translate requirements into data-driven solutions.
Visualization and Communication: Present insights and findings through visualizations and dashboards to inform decision-making.
Innovation: Stay updated on the latest tools and techniques in data science and retail analytics.

Optional Responsibilities (if Experienced)

Feature Engineering:

Engineer and optimize features to improve machine learning model performance.
Automate feature extraction pipelines for scalable workflows.

MLOps:

Contribute to the deployment, monitoring, and retraining of machine learning models in production environments.

Data Engineering:

Assist in designing and maintaining data pipelines and ensuring data quality.

Requirements

Education: Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.
Experience: At least 2 years of experience in data science or a related field.
Technical Skills:

Proficiency in Python for data analysis and machine learning.
Strong SQL skills for managing and querying large datasets.
Experience with machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch).
Knowledge of data visualization tools (e.g., Tableau, Power BI, matplotlib).