Sr. Data Scientist

As a Sr. Data Scientist at our company, you will be responsible for analyzing large datasets, building predictive models, and providing actionable insights that drive strategic decision-making. You will work closely with stakeholders to identify business challenges and translate them into data science problems. Your role will involve extracting insights and building models to understand/predict key metrics, as well as collecting, cleaning, and preprocessing structured and unstructured data from various sources. You will focus on research analysis, model development, and deploying machine learning models to solve real-world business problems. Additionally, you will perform statistical analysis, generate data-driven insights and recommendations, and collaborate with engineering and product teams to implement data solutions. Automating monitoring model performance and retraining will also be part of your responsibilities. Key Responsibilities: - Extract insights & build models to understand/predict key metrics - Work closely with stakeholders to identify business challenges and translate them into data science problems - Collect, clean, and preprocess structured and unstructured data from various sources - Focus on research analysis, model development - Building models (regression, classification, clustering, etc.), validate and deploy machine learning models to solve real-world business problems - Perform statistical analysis and generate data-driven insights and recommendations - Collaborate with engineering and product teams to implement data solutions - Automate monitoring model performance and retraining Required Skills & Qualifications: - Bachelor's or master's degree in computer science, Data Science, Statistics, Mathematics, or a related field - 5+ years of experience in a data science or machine learning role - Strong Python (PySpark, pandas, scikit-learn, TensorFlow/PyTorch) - Hands-on experience with MLflow for model tracking & deployment - Expertise in Databricks for scalable ML workflows - Expertise in handling data issues including data gaps, duplicates, data drifts, etc. - Strong SQL skills and experience working with large databases - Solid understanding of statistical modeling, A/B testing, and predictive analytics - Strong grasp of supervised/unsupervised learning, deep learning, and optimization techniques - Experience with A/B testing and model performance monitoring - Experience with cloud platforms (AWS, GCP, or Azure) and working knowledge of MLOps is a plus - Excellent problem-solving skills, communication skills, and attention to detail - Experience deploying models to production using CI/CD pipelines Preferred Skills (Good to Have): - MosaicML/Azure ML/AWS Sagemaker experience is a plus - Healthcare industry-specific experience In addition to the above, you will enjoy perks such as flexible timings, 5 days working schedule, a healthy environment, celebrations, opportunities for learning and growth, building the community, and medical insurance benefits.,