Data Scientist

For our client – a leader in the insurance industry – we are looking for an experienced Data Scientist.

You will play a key role in developing statistical and machine learning models that support risk analysis, pricing strategies, and data-driven decision-making processes. The role combines advanced analytics with practical business application, contributing to predictive modeling, process optimization, and analytical automation within a complex insurance environment.

The ideal candidate is passionate about data, statistical modeling, and turning complex datasets into clear, actionable insights that create real business value.

Key responsibilities

• Developing and implementing statistical and machine learning models to support risk and insurance-related processes

• Performing exploratory data analysis (EDA) and feature engineering to improve model performance and interpretability

• Analyzing large and complex datasets to generate actionable insights

• Collaborating with business stakeholders to translate analytical findings into practical recommendations

• Working with data processing and visualization tools to communicate results effectively

• Maintaining high-quality, well-structured code using version control systems

Ideal candidate profile

• Strong proficiency in Python for data analysis and modeling

• Very good knowledge of machine learning methods, predictive analytics, and statistical inference

• Hands-on experience with data processing tools (e.g., pandas, SQL)

• Experience with data visualization libraries (e.g., matplotlib, seaborn, ggplot2)

• Experience working with code repositories (e.g., Git)

• Strong analytical thinking and problem-solving skills

• Ability to communicate complex analytical concepts clearly

Conditions

• Location: hybrid in Gdańsk (3 days from the office)

• Contract type: B2B

• Salary: 150–175 PLN/h

• Benefits: private medical care, life insurance, Multisport card

Recruitment steps

• Phone call with a Recruiter (approx. 30 min.)

• Online technical interview with the Client

• Decision and feedback