Data Scientist (Optimization)

The person we are looking for will become part of Data Science & AI Sub- CC Team working within DS&AI competency.   The person will be responsible for delivering projects mainly in optimization/ operations research area, from POCs to scaling up existing solutions, mostly in Supply Chain area for Top500 FMCG companies. Duties include:  • Business understanding, Data understanding/preparation, Modeling, Evaluation and Deployment of solutions – following CRISP-DM methodologies • Understanding optimization methodologies including linear/integer/nonlinear programming and heuristics for finding the best solution to the business problem • Act as ambassador of Lingaro at external Client’s projects   • Be able to deliver technical tasks based on business requirements, from data processing, feature engineering, hypothesis testing and presentation of findings   • Proactive approach for identified areas of improvement  • Following competency/company delivery standards   • Know-how and experience from projects in Supply Chain area, or optimization projects is a plus.  Must have:  • Minimum 5+ years of relevant professional experience • Commercial experience proven by successful projects in the area of data science • Experience in optimization methodologies, including use of various optimization libraries (e.g. CPLEX, Gurobi, ortools, etc.) and eagerness to extend the knowledge  • Strong Python coding skills, including using ML libraries and basic working knowledge of SQL   • Experience in feature engineering techniques and/or usage of external data sources helpful in forecasting problems • Experience working in cloud technologies (MS Azure especially, GCP/AWS nice-to-have) • Familiarity with theory behind various machine learning concepts  • Experience in CRISP-DM projects delivery and with Agile project (like Scrum, Kanban) • Experience in working with client-facing role, specially external clients • Great communication skills Nice to have:  • Other programming languages knowledge like: R, SQL, for Python including Object oriented programming concepts  • Practical knowledge of using genAI  • Understanding and experience in applying Data Science/Machine Learning methods to Supply Chain (Manufacturing, Transportation, Warehousing, Inventory or Sustainability)  • Experience with business requirements gathering, transforming them into technical plan, data processing, feature engineering, models evaluation, hypothesis testing and model deployment • Good understanding of Microsoft Azure technologies or Google Cloud technologies  • Strong statistical/mathematical background – understanding of the math behind ML methods • Good understanding and experience in operationalization of models using VMs • Experience in working in matrix organization • Knowledge about relational databases Our offer: • Stable employment. On the market since 2008, 1500+ talents currently on board in 7 global sites. • “Office as an option” model. You can choose to work remotely or in the office.   • Workation. Enjoy working from inspiring locations in line with our workation policy.  • Great Place to Work® certified employer. • Flexibility regarding working hours and your preferred form of contract.   • Comprehensive online onboarding program with a “Buddy” from day 1.    • Cooperation with top-tier engineers and experts.   • Unlimited access to the Udemy learning platform from day 1. • Certificate training programs. Lingarians earn 500+ technology certificates yearly.  • Upskilling support. Capability development programs, Competency Centers, knowledge sharing sessions, community webinars, 110+ training opportunities yearly. • Grow as we grow as a company. 76% of our managers are internal promotions.   • A diverse, inclusive, and values-driven community.    • Autonomy to choose the way you work. We trust your ideas.   • Create our community together. Refer your friends to receive bonuses.   • Activities to support your well-being and health.  • Plenty of opportunities to donate to charities and support the environment.   • Modern office equipment. Purchased for you or available to borrow, depending on your location.