Design, develop, and deploy machine learning and AI-enabled solutions that support partnering activities such as opportunity prioritization, portfolio intelligence, forecasting, operational insights, and decision support.
Apply advanced analytics, statistical modeling, machine learning, and emerging AI techniques to solve complex business problems and deliver scalable intelligence capabilities across the partnering ecosystem.
Lead exploratory data analysis, feature engineering, model selection, training, validation, and performance evaluation for machine learning and AI-enabled solutions.
Partner closely with business stakeholders and product teams to translate complex business challenges into analytical approaches, machine learning solutions, and scalable intelligence capabilities.
Collaborate with AI, data, and engineering teams to operationalize AI-enabled capabilities and support the adoption of scalable intelligence solutions across partnering platforms and workflows.
Design and develop analytics solutions, dashboards, KPIs, and intelligence capabilities that improve visibility into partnering operations, opportunities, and portfolio activities.
Collaborate with engineering and architecture teams to support operationalization of machine learning and AI-enabled solutions in production environments.
Communicate analytical findings, model outputs, and AI-driven insights through clear visualizations, presentations, and storytelling.

Master’s degree or PhD in Data Science, Computer Science, Statistics, Mathematics, Engineering, Artificial Intelligence, or a related quantitative field.
5+ years of experience in data science, applied AI, machine learning, or advanced analytics solution development.
Strong experience designing, developing, evaluating, and deploying machine learning models for business applications.
Strong proficiency in Python and machine learning/data science frameworks such as scikit-learn, TensorFlow, PyTorch, pandas, and NumPy.
Strong SQL skills for querying, transformation, and analysis of large datasets.
Experience building predictive models, classification models, recommendation systems, forecasting models, or decision-support solutions.
Experience working with structured and unstructured data from multiple sources.
Familiarity with cloud-native AI and analytics platforms such as AWS, GCP, or Azure.
Strong communication and collaboration skills with the ability to work across technical and business teams.

Annual bonus payment based on your performance (target 20%)
Dedicated training budget (training, certifications, conferences, diversified career paths etc.)
Recharge Fridays (2 Fridays off per quarter available)
Take time Program (up to 3 months of leave to use for any purpose)
Vacation subsidy available.
Flex Location (possibility to perform our work from different places in the world for a certain period of time)
Take Time for Charity (additional paid leave of maximum 2 weeks to engage in the charity action of your choice)
Private healthcare (LuxMed packages)
Group life insurance (UNUM)
Multisport
Stock share purchase additions.

Data Scientist – Applied AI

Key skills