Data Scientist

Role overview  We are seeking a talented and passionate Data Scientist to join our dynamic team. In this role, you will leverage advanced analytical techniques and machine learning models to extract actionable insights from our complex data sets, driving strategic decision-making and operational excellence. You will collaborate closely with cross-functional teams to develop innovative solutions that enhance our logistics operations, improve efficiency, and elevate the customer experience.    Key responsibilities  Partner with our product and business teams to understand their needs, translate them into data science solutions, and provide actionable insights  Develop and implement advanced data science solutions (including ML models, AI products, optimization frameworks etc.)  Collaborate closely with cross-functional teams to ensure seamless integration of data-driven initiatives  Stay ahead of the curve exploring cutting-edge methods and being on top of new trends in Data Science & AI  Communicate insights and recommendations to the management and business teams, and other data community members  ​ General requirements  Education – Bachelor’s, Master’s or PhD degree in a relevant field, e.g. data science, computer science, mathematics, statistics, econometrics, physics or similar  Experience – at least 3 years of experience working using data science methods. Strong technical and/or research background is a plus.  Mindset – you are data-driven, goal-oriented and proactive, skilled in change and time management, business-conscious, able to think long-term and decompose business problems  Languages – you are proficient in English (other languages knowledge is a plus)    Nice to have  Experience applying data science methods at scale or building models used in production by large number of users  Previous work on open-source projects  Experience in working in a data-driven environment, designing, executing and analysing many experiments  Specialized knowledge in some of these areas: logistics, operation research, forecasting, spatial data science, graph methods, product analytics or marketing data science    Technical requirements  Excellent knowledge of ML solutions and their impact on business, user experience and operational processes (supervised and unsupervised learning, e.g.: clustering, recommender systems, regression, classification, linear programming, reinforcement learning, time series, geospatial analysis, etc.  Hands-on experience with working with large amounts of data  Proficiency in Python 3, as well as ML and data analysis libraries (e.g. pandas, numpy, scipy, scikit-learn, statsmodels, tf/pytorch, etc.)  Experience in writing well-structured code: functions, classes, modules.  Knowledge and experience in PySpark, relational databases, cloud solutions (e.g. Databricks, Azure, GCP, AWS, Snowflake)    Nice to have  Proficiency in testing code  Knowledge of best practices regarding writing readable code, technical reviews and maintainability  Knowledge of ML Ops and experience with data pipelines framework, preferably Kedro Experience of creating ML models used in production, knowledge of SRE principles  Experience with CLI tools: bash/zsh  Experience in leveraging CI/CD pipelines in data-based products    Benefits Flexible work Contract selection Cafeteria worksmile Language learning platform Conceptual freedom Employee Referral Program Promotion opportunity Initiatives and competitions for employees