Senior Data Scientist

Quick Facts

• Role: Senior Data Scientist

Description

You will turn structured and unstructured customer data into actionable knowledge and measurable business value. The work spans data exploration, building and validating analytical/predictive models, creating visualizations, and delivering insights to stakeholders. You will also design data pipelines for feature engineering and data quality steps, coordinate moderate-to-large projects, and mentor other data scientists.

Responsibilities

• Identify business problems, find the right data and methods to address them

• Process large volumes of structured and unstructured customer data with advanced analytical solutions

• Produce unique actionable insights and business value from analyzed data

• Create high-quality data visualizations

• Build data pipelines for feature engineering, missing value treatment, and outlier detection

• Research, build, and validate analytical, mathematical, econometric, descriptive, and predictive models

• Estimate, plan, and coordinate delivery of moderate/large projects

• Evaluate and select the best matching data science tools and libraries

• Present findings clearly and informatively

• Communicate with stakeholders, product managers, engineers, and other teams about data-driven findings and technical matters

• Continuously develop the team knowledge base and participate in brainstorming sessions

• Educate junior and middle data scientists

Requirements

• 3+ years of relevant experience working with a variety of information systems and data

• High-quality Python coding following PEP-8 guidelines

• Strong data exploration and analysis expertise; ability to build models/analytical frameworks, develop hypotheses, and design experiments

• Advanced knowledge in one domain: Computer Vision, Time Series, Natural Language Processing, Recommendation Systems, or Predictive Analytics

• Knowledge of EDA, classical vs advanced Machine Learning models, model performance metrics and losses, and model fine-tuning

• Knowledge of trade-offs for SOTA ML architectures and when to apply them

• Understanding of ML project life cycle and ability to follow methodologies (CRISP-DM, TDSP, LeanDS, etc.)

• Ability to design and supervise a data labeling process

• Ability to interpret and report analysis results, provide business recommendations, and coach/train others

Benefits

• Hybrid-by-design with opportunity to work remotely within Poland

• Chance to work abroad up to 60 days annually; business-driven relocation opportunities

• Career development programs, mentoring, and soft skills/well-being programs

• Certifications (e.g., Anthropic, Gemini, GCP, Azure, AWS) and English classes

• Stable pay, Employee Stock Purchase Plan with 15% discount

• Health insurance, multisport, shopping vouchers; referral bonuses up to $2,000

• Office amenities and social/well-being events

• Note: benefits apply to employees; B2B contractor terms are agreed individually