Growth through diversity, equity, and inclusion. As an ethical business, we do what is right — including ensuring equal opportunities and fostering a safe, respectful workplace for each of us. We believe diversity fuels both personal and business growth. We're committed to building an inclusive community where all our people thrive regardless of their backgrounds, identities, or other personal characteristics.
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
Minimum 2-4 years for Regular, 4+ years for Lead 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
English: min. B2
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
Missing one or two of these qualifications? We still want to hear from you! If you bring a positive mindset, we'll provide an environment where you feel valued and empowered to learn and grow.
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.
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