Strong Data Scientist

Who we are: Adaptiq is a technology hub specializing in building, scaling, and supporting R&D teams for high-end, fast-growing product companies in a wide range of industries.

About the Product: Our platform is a cloud-based AI-driven workspace that automates statistical analysis validation and generation for clinical research. It serves large pharmaceutical and biotech clients by extracting, validating, and producing complex tabular outputs and regulatory deliverables.

The system handles high volumes of hierarchical tables, figures and listings, applying both classical and generative NLP to accelerate review cycles, reduce manual double-programming and maintain a full audit trail.

About the Role: As a Strong Data Scientist you will own the end-to-end development of novel AI and algorithmic solutions that power our core platform. You will translate research hypotheses into proofs of concept, select and benchmark advanced NLP and tabular-data techniques, and collaborate with engineering teams to integrate your work into production.

Key Responsibilities: Define and drive the AI research roadmap, mentoring peers on practical implementation. Design, develop and evaluate NLP and tabular-data algorithms using GenAI, retrieval-augmented generation (RAG), deep learning, classical ML, NER and rule-based methods. Explore large clinical datasets, perform data cleaning and feature engineering for downstream model training. Build and maintain data pipelines for extraction, transformation and preprocessing of structured and semi-structured inputs. Stay current on state-of-the-art techniques in NLP, generative AI and tabular-data analysis, and integrate best practices. Collaborate with cross-functional teams, including software developers, DevOps engineers to integrate the research solutions into production. Required Competence and Skills: 3+ years of industry experience in NLP and/or tabular-data processing within a production setting. 2+ years of hands-on experience with deep learning methods and frameworks (e.g., PyTorch, TensorFlow). Expertise in both classical NLP (tokenization, NER, parsing, rule-based) and generative NLP (text-to-SQL, table generation, RAG). Advanced Python programming skills and familiarity with data science libraries (pandas, scikit-learn). Proven track record of delivering AI-driven projects into production environments. M.S. or Ph.D. in Computer Science, Machine Learning or a related quantitative field. Strong written and verbal communication in English. Excellent collaboration, interpersonal skills and ability to work independently with minimal oversight. Nice to Have: Familiarity with cloud-based NLP platforms and MLOps tooling. Experience with large-scale table analytics or regulatory statistical outputs.