As a key leader in our data science team, you will define strategy, lead projects, and collaborate with healthcare professionals, engineers, and product teams to deploy scalable AI solutions. Key Responsibilities • AI Model Development: Design, develop, and optimize predictive models for elderly fall risk assessment using advanced machine learning (ML) and deep learning techniques. • Data Analysis: Work with healthcare-specific data (e.g., patient records, sensor data, clinical data) to uncover patterns and actionable insights. • Domain Expertise Application: Leverage healthcare domain knowledge to ensure accuracy, reliability, and ethical use of models in predicting fall risks. • Collaborate with Experts: Collaborate with clinicians, healthcare providers, and crossfunctional teams to align AI solutions with clinical workflows and patient care strategies. • Data Engineering: Develop robust ETL pipelines to preprocess and integrate healthcare data from multiple sources, ensuring data quality and compliance. • Evaluation & Optimization: Continuously evaluate model performance and refine algorithms to achieve high accuracy and generalizability. • Compliance & Ethics: Ensure compliance with healthcare data regulations such as HIPAA, GDPR, and implement best practices for data privacy and security. • Research & Innovation: Stay updated with the latest research in healthcare AI, predictive analytics, and elderly care solutions, integrating new techniques as applicable. • Team Management: Guide all team members in technical and domain-specific problemsolving, manage day to day task deliverables, evaluate individual’s performance and coach. • Stakeholder Management: Present insights, models, and business impact assessments to senior leadership and healthcare stakeholders. Required Skills & Qualifications • Education: Master's or PhD in Data Science, Computer Science, Statistics, Bioinformatics, or a related field. A strong academic background in healthcare is preferred. • Experience: o 8 - 11 years of experience in data science, with at least 2 years in the healthcare domain. o Prior experience in leading AI projects in healthcare startups, hospitals, or MedTech companies. o Ability to work in cross-functional teams. o Ability to publish papers and research findings related to healthcare data science • Technical Expertise: o Proficiency in Python, R, or other programming languages used for ML and data analysis. o Hands-on experience with ML/DL frameworks (e.g., TensorFlow, PyTorch, Scikitlearn). o Experience with time-series data, wearable/sensor data, or IoT data integration is a plus. o Strong knowledge of statistics, probability, and feature engineering. o Familiarity with cloud platforms (AWS, Azure, GCP) and tools for scalable ML pipelines. • Healthcare Domain Knowledge: o Understanding of geriatric healthcare challenges, fall risks, and predictive care strategies. o Familiarity with Electronic Health Records (EHR), wearable devices, and sensor data. o Knowledge of healthcare data compliance (e.g., HIPAA, GDPR). • Soft Skills: o Strong analytical and problem-solving abilities. o Excellent communication skills to present findings to non-technical stakeholders. o A collaborative mindset to work with interdisciplinary teams. Preferred Qualifications • Knowledge of biomechanics or human movement analysis. • Experience with explainable AI (XAI) and interpretable ML models. What We Offer • Opportunity to work on cutting-edge healthcare AI solutions that make a meaningful impact on elderly lives. • Competitive salary and benefits package. • Flexible work environment, with options for hybrid work. • Opportunities for professional growth and leadership. • Collaborative and inclusive culture that values innovation and teamwork. Category Data Analysts Data Scientist Expertise Python - 5 years Azure Data Science Machine Learning - 6 years Data analytics TensorFlow Pytorch

About Think Right Technologies Pvt Ltd

Think Right is a leading provider of data tools that help businesses of all sizes improve scalability, security, and sensibility in their data handling. Our team of experts has a deep understanding of the latest data engineering, AI, research, and data science technologies, and we use this knowledge to create innovative solutions that meet the needs of our customers.