Senior Data Scientist

Quick Facts

• Role: Senior Data Scientist
• Focus: Turning data into actionable knowledge for business problems in the data science domain

Description

You will solve business problems using structured and unstructured customer data, building analytical solutions, models, and data pipelines that deliver measurable business value. The role includes creating data visualizations, selecting appropriate data science tools and libraries, and clearly presenting results to technical and non-technical stakeholders. You will also plan and coordinate moderate to large projects and support the growth of other data scientists.

Responsibilities

• Identify business problems, select the right data and methods to address them
• Process large volumes of structured and unstructured customer data
• Generate 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 data science projects
• Evaluate and select the best-fit data science tools and libraries
• Present findings clearly and informatively
• Communicate effectively with stakeholders, product managers, and engineers about complex findings and technical topics
• Continuously build team knowledge and participate in brainstorming
• Educate junior and middle data scientists

Requirements

• 3+ years of relevant experience working with information systems and data
• Python code quality following PEP-8 guidelines
• Strong data exploration and analysis skills; ability to build models/analytical frameworks, develop hypotheses, and design experiments
• Advanced expertise in at least one domain: Computer Vision, Time Series, Natural Language Processing, Recommendation Systems, or Predictive Analytics
• Knowledge of EDA, classical vs advanced ML models, model performance metrics and losses, and model fine-tuning
• Understanding of the pros and cons of SOTA ML architectures and their applicable use cases
• Understanding of ML project lifecycle and ability to follow methodologies such as CRISP-DM, TDSP, or LeanDS
• Ability to design and supervise data labeling processes
• Ability to interpret and report results, provide business recommendations, and coach/train others

Benefits

• Hybrid work with opportunity to work remotely within Poland
• Chance to work abroad up to 60 days annually
• Business-driven relocation opportunities
• Career development programs and mentoring/soft skills training
• Certifications (Anthropic, Gemini, GCP, Azure, AWS) and English classes
• Stable pay and Employee Stock Purchase Plan with a 15% discount
• Health insurance, Multisport, shopping vouchers, and referral bonuses up to $2,000
• Office amenities and social/well-being events
• Option to work with contractors (B2B terms agreed individually)