Data Scientist

Roles and Responsibilities

• Collaborate with business stakeholders, product managers, and engineering teams to translate business requirements into analytical solutions.
  • Extract and integrate data from multiple sources through APIs, databases, and file-based interfaces.
  • Analyze structured and unstructured data to identify trends, patterns, and actionable business insights.
  • Perform data preprocessing, feature engineering, model development, deployment and model evaluation
  • Evaluate, fine-tune, and optimize AI/ML models to improve accuracy, performance, scalability, and reliability.
  • Develop APIs and services for model deployment and integration with enterprise systems.
  • Ensure data quality, governance, security, and compliance throughout the analytics lifecycle.
  • Stay current with emerging AI, GenAI, machine learning, and data science technologies and recommend their adoption where appropriate

Preferred candidate profile

5 to 8 years of hands-on experience in Data Science, Machine Learning, Predictive Analytics

• Strong proficiency in Python, including experience with data manipulation, statistical analysis, machine learning, and model development using libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch and related frameworks.
• Solid understanding of statistics, probability theory, hypothesis testing, regression analysis, sampling techniques, and experimental design to support data- driven decision making.
• Apply statistical and machine learning techniques to analyze large datasets, identify patterns, build predictive models, and generate actionable business insights.
• Experience in building REST APIs and integrating AI models into production environments.
• Strong understanding of statistics, machine learning algorithms, forecasting techniques, and optimization methods.
• Excellent analytical, problem-solving, and communication skills with the ability to work in cross-functional teams