Key Responsibilities

• Develop, train, and deploy machine learning and predictive models.
• Analyze structured and unstructured datasets to generate insights.
• Build recommendation systems, forecasting models, and classification algorithms.
• Perform data cleaning, preprocessing, and feature engineering.
• Design experiments and evaluate model performance.
• Collaborate with Data Engineers and Business Analysts on data solutions.
• Create dashboards, reports, and visualizations for stakeholders.
• Optimize algorithms and improve model accuracy.
• Work with cloud and big data platforms for scalable analytics.
• Present findings and recommendations to business teams.
• Maintain proper documentation for models and analytics processes.
• Stay updated with emerging AI/ML technologies and industry trends.

Required Skills & Experience

Mandatory Skills

• 6–7 years of experience in Data Science or Machine Learning roles.
• Strong programming skills in:PythonRSQL
• Experience with machine learning frameworks:Scikit-learnTensorFlowPyTorch
• Strong understanding of:StatisticsProbabilityPredictive analyticsData modeling
• Experience with data visualization tools:Power BITableauMatplotlib
• Experience handling large datasets and big data environments.
• Strong knowledge of data preprocessing and feature engineering.
• Familiarity with cloud platforms:AWSAzureGCP

Preferred Skills

• Experience with NLP, Deep Learning, or Generative AI.
• Knowledge of MLOps and model deployment pipelines.
• Experience with Spark, Hadoop, or Databricks.
• Familiarity with Docker and Kubernetes.
• Experience with real-time analytics and streaming data.

Educational Qualification

• Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or related field.
• Relevant certifications in AI/ML or Cloud technologies are preferred.