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Job Summary: We are looking for a highly motivated and analytical Data Scientist / Machine Learning (ML) Engineer / AI Specialist with 1.5 -2 years of experience in Health data analysis, particularly with data sourced from wearable devices such as smartwatches and fitness trackers. The ideal candidate will be proficient in developing data models, analyzing complex datasets, and translating insights into actionable strategies that enhance health-related applications. Key Responsibilities: Develop and implement data models tailored to health data from wearable devices. Stay updated on industry trends and emerging technologies in health data analytics. Ensure data integrity and security throughout the analysis process , correlations relevant to health metrics. Analyze large datasets to extract actionable insights using statistical methods and machine learning techniques. Develop, train, test, and deploy machine learning models for classification, regression, clustering, NLP, recommendation, or computer vision tasks. Collaborate with cross-functional teams including product, engineering, and domain experts to define problems and deliver solutions. Design and build scalable ML pipelines for model development and deployment. Conduct exploratory data analysis (EDA), data wrangling, feature engineering, and model validation. Monitor model performance in production and iterate based on feedback and data drift. Stay up to date with the latest research and trends in machine learning, deep learning, and AI. Document processes, code, and methodologies to ensure reproducibility and collaboration. Required Qualifications: Bachelor's or Master’s degree in Computer Science, Statistics, Mathematics, Engineering, or related field. 1.5-2 years of experience in data analysis, preferably within the health tech sector. Strong knowledge of Python or R and libraries such as NumPy, pandas, scikit-learn, TensorFlow, PyTorch, or XGBoost. Strong experience with data modeling, machine learning algorithms, and statistical analysis. Familiarity with health data privacy regulations (e.g., HIPAA) and data visualization tools (e.g., Tableau, Power BI). Proficiency in SQL and experience working with large-scale data systems (e.g., Spark, Hadoop, BigQuery, Snowflake). Ability to clearly communicate complex technical concepts to both technical and non-technical audiences. Experience with version control tools (e.g., Git) and ML pipeline tools (e.g., MLflow, Airflow, Kubeflow). Experience deploying models in cloud environments (AWS, GCP, Azure). Knowledge of NLP (e.g., Transformers, LLMs), computer vision, or reinforcement learning. Familiarity with MLOps, CI/CD for ML, and model monitoring tools. Experience - 1.5 - 2 years (Only Local Candidates) Location - Mohali Phase 8b Show more Show less
