Data Science

3+ years of experience in a Data Science, machine learning or a related field. Strong hands-on experience in Machine Learning and Statistics focusing on structured and unstructured data problems. Practical experience in several of the following areas: time series forecasting, clustering and classification techniques, regression, boosting algorithms, optimization techniques, NLP, recommendation systems, ElasticNet Excellent programming skills preferably in Python/Py spark and SQL Understanding of developing, implementing, deploying machine learning models on the cloud platforms(Azure, AWS, GCP) by using AWS/Azure Machine Learning, Data bricks, or other relevant cloud services Integrate machine learning models into existing systems and applications, ensuring seamless functionality and data flow Understanding of developing and maintaining MLOps pipelines for automated model training, testing, deployment, and monitoring Understanding of monitoring and analysing model performance, providing reports and insights to stakeholders as needed Familiarity with data processing and storage tools, such as SQL, Hadoop, or Spark Advanced engineering abilities to deliver flexible and scalable end-to-end machine learning solutions. Exposure to data visualization software and packages (Power BI, Tableau, matplotlib, d3) Understands challenges in business area, applicability of relevant data science disciplines, and system interactions. Excellent written and verbal communication skills, confidence in presenting ideas and findings to stakeholders, and ability to do so at the right level of detail. Job Title: Data Science Developer Location: Noida, Bangalore or Kolkata Job Type: Full-time Experience: 3+ years Industry: IT Services & Analytics Your Role and Responsibilities 3+ years of experience in a Data Science, machine learning or a related field. Strong hands-on experience in Machine Learning and Statistics focusing on structured and unstructured data problems. Practical experience in several of the following areas: time series forecasting, clustering and classification techniques, regression, boosting algorithms, optimization techniques, NLP, recommendation systems, ElasticNet Excellent programming skills preferably in Python/Py spark and SQL Understanding of developing, implementing, deploying machine learning models on the cloud platforms(Azure, AWS, GCP) by using AWS/Azure Machine Learning, Data bricks, or other relevant cloud services Integrate machine learning models into existing systems and applications, ensuring seamless functionality and data flow Understanding of developing and maintaining MLOps pipelines for automated model training, testing, deployment, and monitoring Understanding of monitoring and analysing model performance, providing reports and insights to stakeholders as needed Familiarity with data processing and storage tools, such as SQL, Hadoop, or Spark Advanced engineering abilities to deliver flexible and scalable end-to-end machine learning solutions. Exposure to data visualization software and packages (Power BI, Tableau, matplotlib, d3) Understands challenges in business area, applicability of relevant data science disciplines, and system interactions. Excellent written and verbal communication skills, confidence in presenting ideas and findings to stakeholders, and ability to do so at the right level of detail. Required Technical And Professional Expertise Any graduate preferred. 3+ years of Data science experience Strong expertise and deep understanding of machine learning. Strong understanding of SQL & Python. Knowledge of Power BI or Tableau is a plus Exposure to Industry specific (CPG, Manufacturing) use cases is required Strong client-facing skills Must be organized and detail oriented. Excellent communication and interpersonal skills Preferred Technical And Professional Experience Strong foundation in Supervised and Unsupervised Learning (Regression, Classification, Clustering, etc.). Proficiency in Ensemble Learning (Random Forest, Gradient Boosting, XGBoost, LightGBM, etc.). Experience in fine-tuning Large Language Models (LLMs) and working with open-source models (Llama, GPT, BERT, etc.). Familiarity with Prompt Engineering, RAG (Retrieval-Augmented Generation), and Fine-tuning techniques. Hands-on experience with Cloud Platforms (AWS, GCP, Azure) for ML model deployment. Familiarity with MLOps and Model Deployment using Kubernetes, Docker, and MLflow. About Polestar As a data analytics and enterprise planning powerhouse, Polestar Solutions helps its customers bring out the most sophisticated insights from their data in a value-oriented manner. From analytics foundation to analytics innovation initiatives, we offer a comprehensive range of services that help businesses succeed with data. We have a geographic presence in the United States (Dallas, Manhattan, New York, Delaware), UK(London) & India (Delhi-NCR, Mumbai, Bangalore & Kolkata) and have 600+ people strong world-class