Description:
In this role, you design, develop, and apply advanced data science, statistical, and machine learning methods to solve complex, business-critical problems. Embedded directly within customer environments and fast-moving delivery teams, you translate strategic and operational challenges into rigorous analytical solutions at speed. You work closely with customers to deliver scalable, enterprise-grade outcomes that drive measurable business value. You are accountable for the quality, impact, and delivery of complex analytical initiatives — acting as a subject-matter expert, managing ambiguity, and ensuring data-driven solutions are robust, reliable, and aligned with business objectives.
In This Role, You Will
- Transform complex business challenges into data-driven intelligence by identifying high-value problems, framing them analytically, and engineering robust features and insights.
- Design, develop, train, and implement mathematical models, algorithms, and machine learning solutions to solve complex business problems.
- Apply advanced techniques across exploratory analysis, statistical modeling, experimentation, forecasting, segmentation, anomaly detection, causal analysis, and machine learning.
- Integrate analytical and machine learning solutions into products, prototypes, or business processes, ensuring enterprise-grade scalability and robustness.
- Define success metrics, quantify business impact, and translate analytical results into clear, actionable recommendations for decision-makers.
- Lead or manage complex analytical workstreams or projects, including deliverables, milestones, risks, and escalations, as appropriate.
- Communicate insights, trade-offs, and recommendations effectively to cross-functional teams and customer stakeholders, influencing decisions through evidence and expertise.
- Work in an embedded, customer-facing setup, collaborating closely with customer teams to deeply understand their data, applications, and business context — co-developing impactful data and AI-driven solutions.
What You Bring
- Expert-level proficiency in data science and machine learning, with strong command of Python and SQL, and the ability to design, validate, and optimize end-to-end analytical and ML solutions.
- Hands-on expertise with Python and ML frameworks such as TensorFlow, PyTorch, Scikit-learn, and XGBoost.
- Deep applied knowledge of statistics and experimentation, including hypothesis testing, experimental design, causal inference, and uncertainty interpretation.
- Proven experience applying a wide range of ML techniques — classification, forecasting, clustering, recommendation systems, anomaly detection — balancing accuracy, robustness, interpretability, and usability at scale.
- Strong capability to translate ambiguous business questions into measurable analytical problems and connect model outputs to commercial, operational, or strategic decisions.
- Experience delivering production-ready analytics and ML systems on modern data platforms, with a strong focus on data quality, governance, and reusability.
- Exposure to SAP data landscapes including SAP S/4HANA, SAP BW/4HANA, SAP HANA Cloud, and familiarity with SAP Business Technology Platform (BTP), AI Core, AI Launchpad, and SAP AI services.
- Ability to operate effectively in an Agentic AI context, contributing to the design, application, and responsible use of AI agents within complex business processes.
- Advanced communication and collaboration skills, with the ability to influence senior stakeholders through clear data narratives and executive-ready insights.
- You proactively leverage AI in everyday workflows, ensuring high-quality outputs through thoughtful context design and system integration.