Lead Data Scientist, Poland

Warsaw, Masovian Voivodeship, Poland

Applications have closed
Surprise.com logo

Surprise.com

Surprise.com is on a mission to turn the magical, uplifting experience of Surprise into a daily, weekly, and monthly life event – because it makes people happy. Our Surprise Box, and delightful companion app, is the most exciting way to get amazing goodies from brands you love and brands you’re about to love. With daily games, the ability to send and get Surprises from friends, and Grand Surprises – every day is filled with wow!

Surprise is looking for a technically strong, energetic, highly collaborative, and passionate Lead Data Scientist. You will lead and mentor a team of high performing data scientists, ML scientists and ML engineers and shape our growth strategy through empirical studies and experimentation. So, if you're ready to make a big impact in a fast-paced, rapid-growth environment, we want to hear from you!

What will you be doing?

  • Leading a team of Data Scientist;
  • Researching, designing, and implementing machine learning algorithms;
  • Communicating results, technical constraints, and decisions to the business and non-specialists;
  • Communicate and collaborate across teams to drive work forward;
  • Delivering rapid prototypes and proof of concepts that demonstrate real value;
  • Creating and delivering progress reports, slide decks, proposals, and documentation.
  • Design and coordinate scalable and agile data science systems - from data capture to ML service.

What are we looking for?

  • A BS or higher in computer science or a related field;
  • 6+ years of experience in software development;
  • 5+ years of experience in Data Science;
  • Experience in Leading a team of Data Scientists;
  • Extensive knowledge of and practical experience in Machine Learning, Recommender Systems, NLP and other Applications of Algorithms;
  • Practical experience with high-level programming language like Python and DS frameworks;
  • Proficiency in database query languages such as SQL;
  • Understanding of the ETL process;
  • Knowledge of Linear Algebra, Probability and Statistics, and Numerical methods;
  • Practical experience with the software development process, Agile approach, CRISP-DM, and CI/CD.
  • Upper-Intermediate English or higher (B2+).

What skills will come in handy?

  • Experience building large-scale recommender engines (collaborative filtering, KNN, associative rule learning, custom similarity metrics, etc.);
  • Understanding of predictive analytics (time-series analysis and forecasting, survival and duration analysis, etc.);
  • Ability to apply graph analysis techniques for structural pattern recognition;
  • Applied statistics skills, such as distributions, hypothesis testing, regression analysis, etc.;
  • Experience building microservices and containerized applications (Docker, k8s);
  • Familiarity with Big Data frameworks;
  • Experience with mining of structured, semi-structured, and unstructured data;
  • Experience with Feature Stores for ML;
  • Experience with data visualization and BI tools, such as Tableau, Plotly, etc.

Benefits

  • Ultramodern offices in the heart of Warsaw;
  • Work on interesting and challenging projects, while building a pioneering software category;
  • Great atmosphere, with the vibe and energy of a high-growth tech company;
  • Competitive salaries;
  • Close collaboration between international team members;
  • Corporate activities and parties;
  • 20 Paid Time Off days, Public Holidays of Poland;
  • And, of course, we use Surprise internally!

* Salary range is an estimate based on our salary survey at salaries.ai-jobs.net

Tags: Agile Big Data Data visualization Docker ETL Machine Learning Microservices ML NLP Python Recommender systems SQL Statistics Tableau Testing Unstructured data

Perks/benefits: Career development Startup environment Team events

Region: Europe
Country: Poland
Job stats:  8  0  0

Other jobs like this

Explore more AI/ML/Data Science career opportunities

Find open roles in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), Data Engineering, Data Analytics, Big Data, and Data Science in general, filtered by job title or popular skill, toolset and products used.