Senior Data Scientist

Role Overview

• Play a pivotal role in the development and deployment of cutting-edge Gen AI models and solutions
• Responsible for building, testing, and maintaining our Gen AI, RAG and NLP solutions
• Work throughout the whole life cycle of data science projects: design, implementation, production and beyond
• Deliver efficient and production-ready Python code
• Collaborate closely with developers to deploy and productionize our data science pipelines
• Collaborate with subject matter experts in biology and chemistry domains to validate the output
• Data collection, data analysis, model development, defining quality metrics, quality assessment of models and regular presentations to stakeholders
• Create production-ready Python packages for each component of data science pipelines (such as pre-processing and model inference) and their deployment together with software engineering team
• Optimize and customize Retrieval Augmented Generation (RAG) pipelines to meet specific project requirements that involve content ingestion, machine translation, and contextualized information retrieval
• Ingest, preprocess, and transform large-scale multilingual data to ensure high-quality inputs for downstream models
• Build AI agentic models integrated with RAG pipelines
• Conduct rigorous testing and evaluation of AI models to ensure high performance and reliability
• Integrate data science components and perform end-to-end quality assessments
• Maintain robustness of data science pipelines against model drift and ensuring consistent output quality
• Establish reporting processes for pipeline performance and develop automated re-training strategies for existing pipelines
• Collaborate with cross-functional teams to integrate AI solutions into existing products and services
• Lead and manage projects with a team of data scientists and independently execute the entire small-scale projects
• Mentor junior data scientists and foster a knowledge-sharing culture within the team
• Stay up-to-date with the latest advancements in AI, machine learning, and NLP technologies.

Requirements

• Master’s or Ph.D. in Computer Science, Data Science, Artificial Intelligence, or a related field
• 5+ years of relevant applied experience in data science, with a focus on Generative AI, NLP, and machine learning
• Proficiency in Python for data analysis, model development, and deployment
• Strong experience with transformer models
• Proficiency in Generative AI technologies, including utilizing LLMs via API access, LLM evaluation tools, and prompt engineering
• Knowledge of various RAG pipelines and their practical implementation
• Experience building Agentic RAG systems is strong requirement
• Experience with AI agent management frameworks such as LangChain, or similar tools
• Experience with advanced algorithms in deep learning, neural networks, reinforcement learning, and transfer learning
• Familiarity with traditional machine learning algorithms such as random forests, SVM, logistic regression, and Bayesian modelling for model building, validation, and testing
• Familiarity with cloud platforms (e.g., Bedrock, AWS, Azure) for model deployment and the creation of production-ready pipelines
• Proficiency in data visualization tools and techniques
• Experience with version control systems (e.g., GitLab or GitHub), Jira, and working in an Agile environment
• Proficient in using OpenSearch and Databricks
• Excellent problem-solving and analytical skills, with strong attention to detail
• Strong communication skills and the ability to work effectively in a team-oriented environment.

Tech Stack

• AWS
• Azure
• Cloud
• Python

Benefits

• Flexible working hours
• Wellbeing initiatives
• Shared parental leave
• Study assistance
• Sabbaticals