Duties: We are hiring a Head of Data Science with broad experience and deep expertise in applying machine learning to real-world problems. You will develop and communicate hypotheses, analyses, results, ecosystem trends and ultimately innovative solutions to various stakeholders. You will work cross-functionally with several teams including engineering crews, product teams, and program managers. As a part of Industry Solutions Engineering (ISE), at the AI Acceleration Studio we work closely with senior executives and cross-functional teams as we bring design, data science, and engineering to jointly develop cloud-based solutions that have high impact and can accelerate the organization. We work in collaboration with Microsoft product teams, partners, and open-source communities to empower our customers to do more. We pride ourselves on making contributions to open source and making our platforms easier to use
Requirements: Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field and 8+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)

Duties: In this role, your work on the team will primarily be in applying advanced analytics to enable better commodity risk management decisions. For example, you might work as the lead in maintaining and expanding existing hedging strategies by re-training existing models through process driven approaches. You might also modify and improve algorithm performance across market regimes, by introducing new features, data sources, and modelling approaches; rapidly identify opportunities for our clients to increase earnings potential and reduce downside risk by back testing various risk management strategies; co-build bespoke tools with client data science teams that tailor machine-learning algorithms to attain an optimal balance of earnings and volatility given clients’ risk appetite and capital constraints; and/or collaborate with and train cross-functional client teams to instill long-lasting capabilities and ensure new decision-making models are embraced by organizations
Requirements: Undergraduate degree is required; advanced degree in a quantitative discipline such as computer science (especially machine learning), applied mathematics, economics, quantitative finance or engineering is preferred or equivalent practitioner experience; 2+ years of commodity markets experience developing trading or hedging strategies (especially physical/cash markets) or price-discovery analysis in basic materials/metals, agriculture, softs, chemicals, plastics or oil & gas preferred; Experience writing clean, efficient Python code involving model development and deployment using state-of-the-art tools and libraries (e.g. scikit-learn, pandas, etc.)

Duties: Act as lead and main point of contact related to Statistics for designated compound/indication; Follow scientific and technical progress within the field of biostatistics in drug development and advise of new methodologies that may support innovation and improve efficiencies; Engage with regulatory authorities on compound/indication level discussions; Acts as a role model; Ensures consistency of statistical methods and data handling across trials; Ensures all compound/indication related work and information is shared between biostatisticians involved in the compound and with the vendor
Requirements: Master's or PhD in a statistical field with 8+ (AD) and 12+ years (Director) of experience in relevant technical area; Experience in statistical analysis, modelling and simulation and adaptive trial designs; Experience with drug development in biologics, targeted therapies, and companion diagnostics preferred; Experience working with FDA, EMA, and ICH guidance for drug development pertaining to statistics; Experience with the relevant regulatory requirements for biostatistics processes and SOPs

Duties: Design, develop and deploy reproducible data pipelines using cloud-native tools. All our pipelines use infrastructure as code, have automated tests and are as re-usable and reproducible as possible; Connect with collaborators (scientists, project managers, etc.) to translate their needs and questions into technical requirements. We then use the requirements to build data pipelines and visualizations that are meaningful, comprehensible, and practical for them; Every data engineer has projects to lead and others in which there are only smaller contributions; Generate comprehensive documentation of the data products developed, both for technical and non-technical users; Promote good (coding/data) practices and lead by example
Requirements: MS/PhD or equivalent experience in Computer Science, Bioinformatics, or related field; 3+ years of demonstrated working experience as a data engineer; Experience with data pipeline design and creation is a must. The pipelines should use good coding practices and the right tool for the job. Experience with ETL jobs (e.g. AWS Glue, Databricks jobs, AWS Lambda) and orchestrators (e.g. AWS StepFunctions) is desirable; Solid experience in database design (partitions, schemas, choosing database type, etc.) and querying languages (SQL, pyspark or similar) is a requirement. Experience with delta lake (delta tables) is a plus

Duties: Coordinates, provides and delivers methodological and statistical expertise and/or statistical analyses for clinical studies in EPD. In this matter supports both the Clinical Development portfolio as well as Strategic Medical Affairs in their support to Affiliates, thereby complying with international, regulatory guidelines and EPD policies and standards. Directs the operational aspects of statistical work as outsourced to CROs
Requirements: MSc./PhD in Statistics, or Biostatistics, or a related field; Demonstrated high competence in experimental design and statistical inference. Thorough understanding of International Conference on Harmonization (ICH) Guideline and relevant regulatory requirements (e.g., EU, US, or China). Minimum 7 years experience as Statistician in pharmaceutical industry or CRO

Duties: Conducting applied scientific research to advance the organization's technological capabilities in the field of Repair Processes and Reverse Engineering of industrial Rotating Equipment; Conducting project-based research into possible improvements to existing processes and systems; Proposing technical improvements for repairs and new parts of gas turbines and other Rotating Equipment; Coming up with solutions for the iterative steps during the work patent work arounds; Make decisions about the reliability of calculated solutions
Requirements: Bring a Master’s degree in Mechanical Engineering; To have 3 years of relevant work experience in the area of Industrial Engineering; Have specific knowledge of and experience with Computational Fluid Dynamics (CFD) as a must-have; Preferably have knowledge of working with the Finite Element Method (FEM) with Ansys, which is pro; Preferably have knowledge of and experience with Model Analyses and Root Cause Analyses (RCA); Be fluent in written and spoken English; additional language skills in German and/or Dutch are a pro