Data Scientist

• Develop, validate, and deploy statistical and predictive models that directly influence pricing, matching, and growth decisions.
• Develop and improve LLM-powered features, from RAG pipelines to applications of new AI technologies.
• Ensure the reliability of our AI features: design workflows to evaluate performance, measure output quality, and detect regressions.
• Translate open questions into testable hypotheses and design experiments (e.g., A/B tests) that deliver clear, decision-ready answers.
• Analyze funnels and user journeys to identify drop-offs and friction points, and quantify where supply and demand can be better aligned.
• Collaborate with performance marketing to optimize targeting and campaign efficiency using data.
• Define key KPIs, build dashboards, and monitor them to make business impact visible and measurable.
• Document, prioritize, and communicate progress in Jira across product, engineering, and marketing.

Data Scientist – AI, Experimentation

• Machine learning in the credit process: You develop machine learning models that directly support decision-making in the consumer installment loan business.
• You use modern methods from data science, predictive analytics and artificial intelligence (AI).
• AI product features (nice to have): Ideally you help build initial AI features and LLM-based applications that are integrated into our digital installment loan processes.
• Collaboration with data and product teams: You work closely with Data Engineering, Product Management and Data Analytics and use our existing data foundation to develop scalable ML solutions.
• End-to-end responsibility: You take ML models from concept through development, evaluation and deployment to production readiness and continuous optimization.
• Further development of our AI capabilities: You bring in new approaches from machine learning and artificial intelligence and support the advancement of our data-driven products and use cases.

Senior Data Scientist – AI, ML, FinTech

• Shape Redcare’s MDM operating model, connecting different domains through continuous improvement, federated governance, and scalable MDM processes.
• Lead focused MDM initiatives from design to adoption, defining success criteria around data quality, stakeholder engagement, compliance with applicable laws and policies, and architectural fit.
• Lead cross-functional delivery for MDM, from integration initiatives with Data Architecture and Data Engineering teams to alignment with business stakeholders, data owners, and data stewards.
• Design the governed golden record layer, translating business processes into modern data management flows (e.g. matching and merging records, handling exceptions, and defining confidence thresholds) with a strong focus on automation and human-in-the-loop validation.
• Establish recurring data quality management around critical data elements, from profiling, DQ benchmarking, and data cleansing to issue management, remediation workflows, dashboards and KPIs that make progress visible.

Senior Master Data Management Lead

• Bridge the gap between unstructured, real-world data, and frontier AI models
• Serve as the technical link during conversations with global partners to standardise and harmonise data pipelines
• Structure clinical datasets within the STELA program
• Write reproducible code, enforce incoming data QC, and design data dictionaries and ontologies
• Participate directly in technical conversations with external partners (hospitals, research institutions, CROs/CMOs)
• Translate ambiguous source data into harmonized, AI-ready assets
• Map and align diverse clinical data to industry-standard biomedical ontologies
• Design, build, and maintain data dictionaries, schemas, and metadata models
• Establish, automate, and enforce data quality control (QC) frameworks
• Write production-grade Python code to automate data cleaning and harmonization tasks
• Actively audit data to identify missing variables, anomalies, and hidden biases
• Familiarity with cancer progression metrics.

Senior Clinical Data Manager

• Shape the future of insights and business value through data.
• Lead transformation, enable AI, and deliver real business impact.
• Take ownership of a complex data landscape, build and optimize data and knowledge management in our Human Pharma Business.
• Drive transformation initiatives and empower teams.
• Position data as a critical driver of business insights and as the foundation of analytics and AI.
• Focus on driving automation, at scale delivery, and performance across all data management to support business growth, efficiencies and agility.
• Ensure scalable, interoperable data products and solutions that enable AI & analytics across multiple domains.
• Establish robust structures for seamless integration of diverse data sources for actionable insights.
• Accountable for ontology & semantic delivery and management.
• Oversee the end-to-end data lifecycle, ensuring data quality, integrity, and security.
• Collaborate closely with IT and business stakeholders.

Head of Data Operations – Data Product

• Technical implementation of our Data & AI projects end-to-end
• Build scalable data infrastructure
• Transition AI use cases into production
• Hands-on engineering (Python, SQL, PySpark, APIs)
• Lead, coach and develop an interdisciplinary team

Data Science Manager

• Be part of our Data Science team to further optimize our innovative product based on machine learning and artificial intelligence
• Work on advanced and demanding AI fields such as large language models
• Identify, understand, structure and solve complex problems in a driven and pragmatic manner
• Work on projects that deliver measurable value to our business
• Experiment with new technologies and acquire new skills to find clever solutions to the unique challenges we will encounter along the way
• Communicate between all stakeholders (data scientists, lead developers, product management, business owners) and present technical product concepts

Senior Data Scientist – f/m/d

• Growth and development: With your extensive experience in business development, you will expand our presence in the Data & AI market, develop market segment strategies, and lay the foundational prerequisites for the long-term growth of our team.
• Partnerships and network: Thanks to your experience and expertise, you can easily identify and maintain relationships and partnerships with key stakeholders in Financial Services, in particular insurance, capital markets and banking.
• Market analysis and opportunities: You are adept at analyzing market trends, competitors and customer feedback to identify growth potentials and opportunities and to further shape Accenture’s product portfolio and offerings.

Senior Manager, AI & Data – Financial Services

• Develop a comprehensive concept for sustainability data management, including data collection, automation, and system architecture
• Lead the implementation of tools, systems, and KPIs for group-wide sustainability governance (e.g., ESG reporting, Product Carbon Footprint)
• Build a scalable and transparent data landscape in close collaboration with Controlling, IT, and other corporate functions
• Support operational units, ensure data quality, and create transparency in progress measurement and reporting
• Communicate clearly and effectively with internal and external stakeholders (e.g., Heraeus ESG Steering Board)

Senior Manager, Group Sustainability – Data, Systems & Tools

• Own and extend our offline eval suite across products — datasets (capability + regression), judges, metrics
• Build and maintain online quality dashboards: resolution rate, CSAT, thumbs up/down, LLM-as-judge signals, error rate, latency
• Close the production feedback loop: mine failure patterns from real traffic → turn them into regression cases → propose fixes to Product and domain experts
• Harden methodology: judge stability, non-determinism handling
• Translate numbers into decisions – weekly syncs, clear trade-offs, no dashboards for their own sake

Product Data Scientist – AI Evaluation, Quality

• You will take a leading role in strategically advising our clients on modernizing BI, reporting, and visualization landscapes — from target vision to sustainable implementation.
• You will be responsible for end-to-end Data & AI transformation programs with a focus on measurable business impact, decision quality, and lasting value.
• You will advise top management and senior stakeholders on BI and analytics strategies, data culture, and AI-enabled decision-making and visualization concepts (e.g., Augmented Analytics, Conversational AI).
• You will act as a trusted advisor at the executive level, lead steering committees, strategy workshops and executive alignments, and guide interdisciplinary teams across all project phases.
• You will actively drive business development, own pitches and business cases, build long-term client relationships, and position Accenture as a thought leader in BI & AI transformation.

Data Visualization Manager – AI, Big Data

• Guide participants during the practical phase while they work on tasks and projects in Data Science and AI
• Support with technical questions and explain concepts
• Assist participants in independently developing solutions
• Identify knowledge gaps and provide targeted support in the learning process
• Provide supplementary learning prompts and resources
• Contribute to the improvement of tasks and to a positive learning atmosphere in the course

Working Student Tutor in Data Science, Artificial Intelligence

• Recruit, onboard, and develop a high-performing team of Account Executives
• Own the revenue forecast and GTM strategy for Austria and German Mid-Market
• Drive a culture of "data care" by ensuring meticulous CRM maintenance
• Masterfully apply structured sales methodologies to close complex deals
• Act as a bridge between the Data Foundation specialist team and Salesforce Core teams
• Leverage your existing network to build C-suite relationships

Regional Vice President – Head of Austria & Mid-Market Germany, Data Foundations

• Operate at the intersection of data engineering, clinical science, and partner collaboration across two strategic domains:
• Technical conversations with external partners (hospitals, research institutions, CROs/CMOs) and dive into the details of diverse clinical data structures.
• Translate ambiguous source data into harmonized, AI-ready assets.
• Map and align diverse clinical data to industry-standard biomedical ontologies.
• Design, build, and maintain data dictionaries, schemas, and metadata models.
• Establish, automate, and enforce data quality control (QC) and validation frameworks for incoming partner data.
• Write production-grade Python code to automate data cleaning and harmonization tasks.
• Practical understanding of how clinical data is generated in the real world.
• Identify anomalies and hidden biases in incoming data.

• Own the end-to-end relationship with Upvest’s market data and static asset data providers.
• Lead commercial negotiations independently and end-to-end, from initial terms through to signature and renewal.
• Ensure that Upvest’s redistribution of market data to B2B clients is properly licensed across all use cases and client types.
• Fulfill entitlement and usage reporting obligations to direct reporting exchanges and data sources. Maintain accurate records of Upvest’s data consumption and distribution to support audit readiness at all times.
• Act as the expert voice on market data licensing for internal teams advising on what data products clients can access, at what cost, and under what licensing conditions.
• Lead the assessment, selection, and onboarding of new market data providers and exchanges as Upvest expands into new asset classes and markets.
• Establish and maintain best-practice governance processes for market data management.
• Identify cost-saving opportunities through licence renegotiation, consolidation, or usage optimisation.
• Monitor policy and commercial changes from exchanges and vendors, assess their impact on Upvest, and proactively communicate material developments to relevant stakeholders.
• Provide support in the management of other Network partners where needed, working closely with the Head of Network to ensure consistent partner oversight across the team.

Senior Data Governance Manager

• Define and continuously evolve the strategic value proposition of Statista's insights offering, ensuring its relevance and differentiation in an AI-dominated world
• Drive automation across the insights production workflow to significantly increase output while optimizing team capacity and resource allocation
• Design and implement scalable, AI-first processes that enable your teams to produce insights more efficiently without compromising on quality
• Establish and manage systematic quality assurance frameworks that ensure the accuracy, consistency, and editorial standard of all published insights
• Own topic setting and editorial direction, aligning closely with data production and general production steering to ensure a coherent strategy across the organization
• Collaborate with the Data Engineering team to build and continuously improve the tools, pipelines, and scalable infrastructure needed to support automated insights production
• Leverage analytics and customer usage data to evaluate the impact of published insights, inform topic prioritization, and thus drive measurable value for Statista's users
• Lead, develop, and empower six Team Leads, fostering a culture of ownership, continuous improvement, and cross-functional collaboration

Head of Data Insights Operations

• Own LLM/ML pipelines for extraction, classification, anomaly detection, and recommendations.
• Define evaluation & monitoring: gold sets, automated tests, robustness checks, SLAs, and cost/latency tracking.
• Productionize with Platform/Data Eng: bring your models live and iterate/improve until they are adopted by your stakeholders.

• Lead marketing and sales activities related to ABB’s products, systems, and services within the Data Center industry segment in Germany.
• Ensure that the division and related sales units substantially improve their sales performance, profitability, market share, and customer satisfaction.
• Develop and implement a market-based strategy for the DC segment — including direct, third-party, and project-based sales.
• Drive cross-division and cross-region collaboration to strengthen ABB’s market presence.
• Coordinate and steer Data Center projects within the German and international ABB organization.
• Expand and strategically develop the Data Center segment in Germany.
• Develop application concepts in medium voltage, low-voltage switchgear (NSHV), and UPS systems.
• Build strong relationships with key customers and external stakeholders.
• Design and execute marketing campaigns and plans in collaboration with German and international marketing teams.
• Represent ABB in relevant industry associations and working groups.
• Activate market intelligence and benchmarking to identify industry trends, product gaps, and competitor strategies.

Segment Manager, Data Center

• Own the end-to-end GoSilico product lifecycle—roadmap, feature prioritization, release planning, versioning, and end-of-life
• Execute qualitative and quantitative VOC—including for emerging data and digital service concepts—build customer segmentation and personas
• Lead the productization and commercialization of data-driven offerings emerging from the Digital Modelling roadmap
• Build cross-functional relationships across and within Cytiva and Danaher business unit functions

Senior Global Product Manager, Digital Modeling, Data Products

• Define and execute Hilo's Business Intelligence strategy, enabling data-informed decision making across the organisation.
• Act as a strategic partner to Finance, Product, Commercial, Clinical and Leadership teams.
• Translate complex business challenges into scalable analytics solutions and actionable insights.
• Own the evolution of Hilo's BI capability, driving reporting excellence, data governance and self-service analytics.
• Deliver timely, accurate and actionable insights that support operational and strategic decision making.
• Collaborate with business leaders to identify analytical opportunities and define reporting requirements.
• Drive adoption and continuous improvement of reporting and analytics tools across the organisation.
• Monitor and enhance reporting performance, usability, and stakeholder satisfaction.
• Maintain, establish BI standards, governance frameworks, and best practices to ensure consistency, scalability, and reliability across analytics solutions.
• Champion a data-driven culture across the organisation by promoting the effective use of data in decision-making.

Data Scientist jobs in Germany

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Data Scientist – AI, Experimentation

Senior Data Scientist – AI, ML, FinTech

Senior Master Data Management Lead

Senior Clinical Data Manager

Head of Data Operations – Data Product

Data Science Manager

Senior Data Scientist – f/m/d

Senior Manager, AI & Data – Financial Services

Senior Manager, Group Sustainability – Data, Systems & Tools

Product Data Scientist – AI Evaluation, Quality

Data Visualization Manager – AI, Big Data

Working Student Tutor in Data Science, Artificial Intelligence

Regional Vice President – Head of Austria & Mid-Market Germany, Data Foundations

Senior Clinical Data Manager

Senior Data Governance Manager

Head of Data Insights Operations

Senior Data Scientist – f/m/d

Segment Manager, Data Center

Senior Global Product Manager, Digital Modeling, Data Products

BI & Strategic Analytics Lead