Job
Description
Role Overview: As a Data Science Lead for Clinical Intelligence at Anervea, you will play a crucial role in spearheading data operations for the clinical intelligence SaaS platform. Your responsibilities will include leading the development of data pipelines, integrating computational biology insights, ensuring compliance with US pharma regulations, and driving AI-powered predictions for patient outcomes across various therapies like oncology and diabetes. This position is ideal for a leader with expertise in computational biology, clinical research, and scalable data systems. Key Responsibilities: - Build and manage end-to-end data pipelines for ingesting and analyzing de-identified real-world evidence (RWE), preclinical data, and public datasets (e.g., TCGA, ChEMBL) using Python, pandas, and cloud tools. - Ensure data quality, privacy, and compliance with regulations such as HIPAA, FDA (21 CFR Part 11), and GDPR, with a focus on de-identification and bias mitigation. - Lead the integration of computational biology (e.g., genomics, AlphaFold protein modeling) into AI models for therapy-agnostic outcome predictions. - Collaborate with AI teams to develop predictive models (e.g., XGBoost, PyTorch) for clinical trials and personalized medicine. - Optimize data operations for scalability and cost-efficiency, specifically handling large and diverse health datasets. - Oversee cross-functional teams (remote/hybrid) to troubleshoot issues, audit data, and deliver client-ready insights. - Stay updated on US pharma trends (e.g., real-world evidence, precision medicine) to enhance platform capabilities. Qualifications and Requirements: - Masters or PhD in Computational Biology, Bioinformatics, Data Science, or related field. - 4+ years of experience in data science or operations within the US pharma/biotech industry, with expertise in clinical research such as trials and real-world evidence. - Deep knowledge of computational biology, including genomics and RDKit/AlphaFold for drug-protein interactions. - Proficiency in Python, SQL, ETL tools (e.g., Airflow), and big data frameworks (e.g., Spark). - Familiarity with US pharma regulations (HIPAA, FDA) and clinical trial processes (Phase 1-3). - Experience with AI/ML applications for health data, such as scikit-learn and PyTorch. - Based in India and open to remote or hybrid work in Pune. - Strong leadership and communication skills for global client collaboration. Additional Company Details: Anervea is a pioneering AI transformation tech company that delivers AI-powered SaaS solutions for the US pharma industry. Their therapy-agnostic clinical intelligence platform utilizes real-world evidence to predict patient outcomes and personalize treatments, enabling clients to optimize clinical trials and accelerate drug development. The company offers competitive salaries based on experience, performance bonuses, flexible remote/hybrid work options, health benefits, learning opportunities, leadership roles in cutting-edge US pharma AI innovation, and a collaborative global team environment. Role Overview: As a Data Science Lead for Clinical Intelligence at Anervea, you will play a crucial role in spearheading data operations for the clinical intelligence SaaS platform. Your responsibilities will include leading the development of data pipelines, integrating computational biology insights, ensuring compliance with US pharma regulations, and driving AI-powered predictions for patient outcomes across various therapies like oncology and diabetes. This position is ideal for a leader with expertise in computational biology, clinical research, and scalable data systems. Key Responsibilities: - Build and manage end-to-end data pipelines for ingesting and analyzing de-identified real-world evidence (RWE), preclinical data, and public datasets (e.g., TCGA, ChEMBL) using Python, pandas, and cloud tools. - Ensure data quality, privacy, and compliance with regulations such as HIPAA, FDA (21 CFR Part 11), and GDPR, with a focus on de-identification and bias mitigation. - Lead the integration of computational biology (e.g., genomics, AlphaFold protein modeling) into AI models for therapy-agnostic outcome predictions. - Collaborate with AI teams to develop predictive models (e.g., XGBoost, PyTorch) for clinical trials and personalized medicine. - Optimize data operations for scalability and cost-efficiency, specifically handling large and diverse health datasets. - Oversee cross-functional teams (remote/hybrid) to troubleshoot issues, audit data, and deliver client-ready insights. - Stay updated on US pharma trends (e.g., real-world evidence, precision medicine) to enhance platform capabilities. Qualifications and Requirements: - Masters or PhD in Computational Biology, Bioinformatics, Data Science, or related field. - 4+ years of experience in data science or operations within the US pharma/biotech industry, with expertise in clinical research such as trials and real-world evidence. - D
