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Data Scientist – Applied AI
RocheData Scientist delivering AI and machine learning capabilities across Roche's Partnering Digital Solutions ecosystem. Collaborating with product owners and teams to improve decision-making and operational efficiency.
Tech Stack
Tools & technologiesAWSAzureCloudGoogle Cloud PlatformNumpyPandasPythonPyTorchScikit-LearnSQLTensorflow
About the role
Key responsibilities & impact- 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.
Requirements
What you’ll need- 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.
Benefits
Comp & perks- 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.
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
machine learningAIadvanced analyticsstatistical modelingfeature engineeringmodel selectionmodel trainingmodel validationperformance evaluationpredictive modeling
Soft Skills
communicationcollaborationstorytellinganalytical thinkingproblem-solving
Certifications
Master’s degreePhD