Data Scientist (GenAI)

PROJECT INFORMATION:

• Industry: Pharma

• Location: hybrid (visit the Warsaw office 1-2/month)

• Remuneration: up to 240 PLN/h netto + VAT (B2B)

• Project language: English

• Start: ASAP

Summary

The Data Scientist role aims to significantly impact by implementing advanced AI solutions in the Product Supply domain. The position is crucial for the management of the entire product life cycle, enhancing data-driven decision-making in a collaborative international team.

Key Tasks & Responsibilities: 

• Creates, employs, and evaluates generative AI, machine learning, and NLP models and workflows that deliver actionable insights and meet business objectives. 

• Strengthens, maintains, and regularly updates developed solutions to ensure optimal performance and reliability. 

• Extracts valuable information from large structured and unstructured datasets, identifying key variables and metrics that influence product supply. 

• Builds prototypes to prove modeling concepts. 

• Industrializes and scales up successful advanced analytics prototypes into IT products. 

• Creates intuitive and interactive data visualizations, reporting tools and dashboards to communicate complex analytical findings to technical and non-technical stakeholders as well as enable scenario creation and management. 

• Develops generalized frameworks and libraries for repetitive data science activities. 

• Participates in exploratory projects that investigate new data sources, tools, and analytical techniques, keeping Client at the forefront of data science in the consumer health sector. 

• Builds data processing pipelines, analyzes data used for modelling and performs other data related activities as required. 

• Manages code in GitHub repositories and performs peer code reviews. 

• Fosters a culture of continuous learning within the data science team, taking active part in workshops and training sessions to share knowledge and skills. 

• Presents compelling data driven stories to all levels of the organization, including peers, senior management, and internal customers to drive both strategic and operational changes in the business. 

• Acts as a subject matter expert in data science, advising on best practices and emerging technologies.  

  
  

Qualifications & Competencies (education, skills, experience): 

• Master’s or PhD degree with experience in Data Science or related fields. 

• Proven educational background or applied experience in at least one of the following: Machine Learning, Statistics, Mathematics, Computer Science, Quantitative Finance/Economics/Marketing, Biostatistics, Bioinformatics, or other related quantitative disciplines.  

• Strong proficiency in Python and its data science and AI libraries (e.g. Pandas, NumPy, LangChain, Scikit-learn). 

• Good proficiency and practical experience in machine learning and generative AI. 

• Good knowledge of data science tools, libraries, frameworks, and platforms: Python, SQL, Vector Stores, Spark, Azure, Databricks, GitHub, LangChain, RAG, prompt engineering.