Translate client requirements into differentiated, deliverable solutions using in-depth knowledge of a technology, function, or platform. Collaborate with the Sales Pursuit and Delivery Teams to develop a winnable and deliverable solution that underpins the client value proposition and business case.
Must have skills :
Generative AI
Good to have skills :
Architectural Design
Minimum
12
year(s) of experience is required
Educational Qualification :
15 years full time education
Sr. Data Scientist / MLE - Prompt Engineering Focus: Hands-on coding and prompting, developing technical architecture, collaborating with Medical Writers, and coaching/quality-checking junior team members. Data Scientist / MLE - Prompt Engineering Focus: Hands-on coding and prompting, working with Medical Writers, and delivering high-quality programming work. Requirements: Proficiency in Python, with hands-on experience using common libraries (pandas, NumPy, OpenAI, scikit-learn). Strong expertise in Prompt Engineering (creating and iterating prompts, fine-tuning LLMs, working with frameworks like LangChain, and potential use of Retrieval-Augmented Generation (RAG)). Experience in preparing and processing unstructured data. Familiarity with AWS services (e.g., SageMaker, S3, DynamoDB). Knowledge of knowledge graphs is a plus. Key Responsibilities: 80% Solution Development (Prompting, GenAI Development) + 20% Deployment Main Solution: Creating Prompts for CSR Generation Collaborate with Medical Writers to translate Clinical Study Reports (CSR) into structured prompts or prompt chains. Refine and iterate prompts to ensure high-quality output. Perform statistical analysis and generate insights to validate prompt outputs. Measure and monitor output metrics for continuous improvement. Develop Python scripts to call LLM APIs (e.g., OpenAI GPT) with the created prompts. Hands-on coding. Data Processing (Documents and Tables) Understand protocols and Statistical Analysis Plans (SAPs), with support from Medical Writers, and process this information into databases or RAG databases. Process tables and store data into databases. Solution Deployment Collaborate with teammates to productionize code and deploy models. Provide or assist in technical architecture design. Work with Medical Writers to create and execute User Acceptance Testing (UAT) scenarios. Ways of Working: Working with the CSR team. Participate actively in standups and working sessions (US Eastern AM). Working Sessions with offshore Medical Writers. Primarily working with the CSR team, with minimal overlap with PSUR and Platform team for this delivery.
15 years full time education
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