Job Description

Key Responsibilities

Analyze large, complex datasets to identify trends, patterns, and actionable insights. Build, train, and validate machine learning and statistical models. Develop predictive algorithms for business forecasting and decision-making. Perform data cleaning, wrangling, and feature engineering to create high-quality input for models. Collaborate with product, engineering, and business teams to solve real-world problems using data-driven methods. Communicate findings through clear visualizations, dashboards, and presentations. Deploy models into production using tools such as MLflow, Docker, AWS/Azure/GCP. Develop and maintain ETL pipelines in coordination with data engineering teams. Conduct A/B testing and model performance evaluation. Stay updated with latest advancements in AI/ML, deep learning, and data science methodologies.
Required Skills & Qualifications

Strong programming skills in Python and/or R. Expertise in machine learning libraries like Scikit-learn, TensorFlow, PyTorch. Solid understanding of statistics, probability, and mathematical modeling. Proficiency in SQL, data manipulation, and working with structured/unstructured data. Experience with visualization tools: Power BI, Tableau, Matplotlib, Seaborn. Knowledge of cloud platforms (AWS, Azure, GCP). Excellent problem-solving, analytical thinking, and communication skills.
Job Type: Full-time

Work Location: In person