Senior Data Scientist

Full time

Employment Information

At Jacobs, we’re challenging today to reinvent tomorrow by solving the world’s most critical problems for thriving cities, resilient environments, mission-critical outcomes, operational advancement, scientific discovery and cutting-edge manufacturing, turning abstract ideas into realities that transform the world for good.

Your impact

At Jacobs, we’re embarking on an exciting journey as we initiate the development of our Digital & Data Hub in the heart of Krakow. Our mission is to undertake projects spanning various industries, including Consumer and Manufacturing, Defence and Security, Energy and Utilities, Financial Services, Government and Public Services, Health and Life Sciences, and Transport. By working together in international teams and with different perspectives, we gain the experience that is our collective strength.

In Jacobs, every day is a chance to make the world a better place - let’s design your career with us!

Key Responsibilities:

  • Design algorithms to infer key transportation patterns from various data sources
  • Research and implement suitable strategies (e.g. regression models, ML models, etc.) for solving data science problems
  • Find and build real-world data sets for training various models and doing quality checks
  • Productize data science algorithms within our platform, in collaboration with the Application Engineering team
  • Create visualizations and dashboards to help tell stories with data
  • Define and implement customized and/or cutting-edge solutions for customers

Here’s what you’ll need

  • BS/MS in Mathematics, Computer Science or an Engineering discipline. Alternatively, a PhD focused on quantitative research and discovering insights from data is acceptable in lieu of a BS/MS plus experience
  • 3-5 years of experience in data science and/or statistics using a coding language (Python preferred)
  • 2+ years of experience in SQL and relational databases (PostgreSQL preferred), and good understanding of relational concepts
  • Strong understanding of techniques in data science (machine learning algorithms, regression analysis, etc.)
  • Strong data analysis skills, knowing what can/cannot be possible, and ability to visualize data in the best way possible
  • Good communication skills - written, visual (presentations), and verbal
  • Ability to deliver adequate results on deadline, and make compromises to enable scalability and productization of algorithms

We offer:

  • Unique company culture fostering individual career growth and work-life balance
  • Full-time employment contract with salary corresponding to qualifications
  • Hybrid working model
  • Flexible working hours (we start between 7:30-10:00)
  • “Short Fridays” (we work 6h on Friday)
  • Flexible benefits package (Lux Med medical care, psychological care, life insurance, My Benefit cafeteria system, including Multisport card co-financing, car park sharing system)
  • Membership in Jacobs employee networks (Women’s Network, OneWorld, PRISM, Careers Network, Green Team, Toastmasters, Collectively and others)
  • Continuous development opportunities, including a range of professional trainings and certifications (e.g. ACCA, CIPS), Graduate Development Program, Learners’ Community, self-learning platform
  • Opportunity to take part in language courses (English, German, Polish)

We know that if we are inclusive, we’re more connected, and if we are diverse, we’re more creative. We accept people for who they are, regardless of age, disabilities, gender identity, gender expression, marital status, mental health, race, faith or belief, sexual orientation, socioeconomic background, and whether you’re pregnant or on family leave. Find out more about life at Jacobs. As a Disability Confident employer, we will interview all disabled applicants who meet the criteria for a vacancy. If you require further support or reasonable adjustments with regards to the recruitment process (for example, you require the application form in a different format), please contact the team


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