Data Scientist

Direct W2 contractors only! No 3rd party agencies! No Visa Sponsorship available! One of our direct clients, a global biotech company in the San Francisco Bay area is looking for a Data Engineer/Data Scientist for a 6 month part-time remote W2 contract . About Our Team: AI Emerging Tech and External Collaborations Join our AI Emerging Technology & External Collaborations team a strategic group focused on delivering AI-driven insights and innovative solutions to advance the Pharma and DIA Partnering business. We operate at the intersection of science, data, and strategy, leveraging emerging technologies, external research collaborations, and advanced analytics to accelerate decision-making and unlock business value. Our work spans a diverse set of high-impact initiatives - from building intelligent data products to developing end-to-end AI/ML workflows that power use cases such as opportunity identification, asset evaluation, and portfolio optimization. As a member of our team, you ll have the opportunity to shape the future of AI at Roche by applying data science to solve complex business problems, collaborating across functions, and influencing global strategic decisions in Partnering. Responsibilities As a Data Scientist, you will play a critical role in shaping our data strategy and solving complex business challenges through the innovative application of machine learning. You will move beyond simply executing on requirements; you will be a thought partner who seeks out opportunities, defines the right questions to ask, and drives projects from ambiguity to impactful business outcomes. As a Data Scientist, you will be a pivotal member of our team, responsible for: Key Responsibilities: End-to-End Model Ownership: Drive the entire machine learning lifecycle, from exploratory data analysis (EDA) and advanced feature engineering to model training, validation, deployment, and post-launch monitoring for performance and concept drift. Problem Formulation: Translate ambiguous business requirements and domain challenges into well-defined technical problems, testable hypotheses, and robust machine learning solutions. Rigorous Experimentation: Design, test, and validate multiple modeling approaches to find the optimal solution, establishing clear and relevant evaluation metrics that directly align with business goals. Technical Implementation & Deployment: Utilize our Triple AI SageMaker environment to efficiently train, deploy, and manage scalable models in a production setting. Data Storytelling & Visualization: Communicate complex model outputs and data-driven insights through compelling storytelling and clear visualizations, empowering business stakeholders to make informed, data-backed decisions. Product-Oriented Mindset: Develop a deep understanding of the business domain and product vision, ensuring that your work is not just technically sound but also delivers tangible and measurable value to the end-user. Collaborative Innovation: Actively collaborate with engineers, product managers, and business leaders, fostering a culture of shared knowledge, open feedback, and continuous improvement. Proactive & Agile Impact: Embody an entrepreneurial spirit and an agile mindset, proactively identifying opportunities for impact and focusing on delivering concrete business results and outcomes over exhaustive documentation. Skills required: Full life cycle M/L project experience resulting in M/L solutions MS in CS, Statistics, Engineering, Math, or other quantitative field 3+years work in an enterprise environment working on M/L models as a data scientist Experience with Python and its data science libraries AWS or other cloud platform Experience building models for business applications like forecasting, clustering, classification Front-end development experience. Generative A/I knowledge