Title: Principal Research Scientist II - Data Architecture, Biotherapeutics and Genetic Medicine Location: Worcester United States - Full-time - Salary Min: 141500 - Salary Max: 268500 - Workday Global Grade: 20 - Travel: Yes, 5% of the Time - Compensation: USD 141,500 - USD 268,500 - yearly Job Description: Company Description AbbVie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas - immunology, oncology, neuroscience, and eye care - and products and services in our Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at www.abbvie.com. Follow @abbvie on X, Facebook, Instagram, YouTube, LinkedIn and Tik Tok. Biotherapeutics and Genetic Medicine (BGM), a part of Discovery Research within AbbVie's R&D, is a global organization that is responsible for discovering and optimizing drug candidate molecules for biotherapeutic modalities (monoclonal antibodies, multispecifics, proteins, conjugates, etc.) and genetic medicines (AAV, LNPs, siRNA etc.) for all therapeutic areas across discovery. Job Description The Principal Data Architect is a visionary leader in the development and success of our cloud-native data platform, which supports the development and integration of predictive and generative machine learning solutions in drug discovery scientist workflows. This role requires a strong ability to see both the big picture and the details, and to work cross-functionally with both wet lab scientists, ML engineers, software engineers, data engineers, and data infrastructure engineers, among others. This position reports to the Head of AI/ML in Biotherapeutics and Genetic Medicine (BGM) and will serve as a trusted advisor to senior leadership. This role is pivotal in driving our organization towards becoming a leader in the application of artificial intelligence, ensuring that AI and ML initiatives are built on a robust, resilient, and scalable data foundation that grows with the organization. Key responsibilities: - Drive the vision, execution, implementation, adoption, and continuous improvement of a robust, scalable data platform as the foundation for the execution of AbbVie's AI/ML strategy, particularly within BGM. - Define data models and architectures that collect, store, structure, access, and connect datasets generated across a dozen different lab groups, enabling downstream uses (ML model development, operational reports, lab documentation, etc.). - Collaborate closely with wet lab scientists, especially the Head of Lab Data Products, and automation engineers to maximize the utility of data captured by lab automation workflows. - Collaborate closely with data scientists, and deployment engineers, to ensure data pipelines support both machine learning model development and deployment into production. - Co-develop and execute a strategy that maximizes FAIR-fication of BGM data and in concert with wider BGM strategic goals. - Communicate the impact of a robust data platform to AbbVie's drug pipeline, using both user stories and KPIs that allow measurement of the value added. - Multiply impact of the data platform by championing and communicating the principles behind connected data, data stewardship, data-as-a-product, and cloud-first and cloud-native architectures. - Collaborate with data infrastructure and data governance experts across AbbVie to ensure that data governance principles and policy are optimally implemented. - Ensure alignment and coordination of data infrastructure initiatives with existing AbbVie initiatives such as Convergence, and ARCH. Qualifications Qualifications: - BS, MS, or PhD in computer science, data science, computational biology, computational chemistry, computational biophysics, or related field with typically 14-16+ (BS) years, 12-14+ (MS) years, or 6-8+ (PhD) years of experience in data architecture with a track record of designing enterprise data platforms. - Deep technical skills in data modeling, data integration, implementation of data storage solutions, data pipelines, and integration with AI/ML. - Production programming expertise in SQL, python, or Java. - Experience building cloud data infrastructure solutions using AWS, Azure, or GCP. - Familiar with both wet and dry lab scientific principles and processes, able to foresee and prevent data platform-originating failure modes. - Experience with cross-functional team leadership, and track record of collaboration excellence. - Previous experience in the pharmaceutical or biotechnology sectors. - Experience managing both team member delivery and career development. - Exceptional interpersonal and communication skills, and strong evidence of ability to build stakeholder alignment. - Ability to integrate data governance principles into everyday decision making. - The position is located at Worcester, MA site as a full time in office or hybrid (3 days per week) role. - Position will be hired based on level of experience - Principal Research Scientist I or Principal Research Scientist II Additional Information Applicable only to applicants applying to a position in any location with pay disclosure requirements under state or local law: - The compensation range described below is the range of possible base pay compensation that the Company believes in good faith it will pay for this role at thetime of this posting based on the job grade for this position. Individual compensation paid within this range will depend on many factors including geographic location,and we may ultimately pay more or less than the posted range. This range may be modified in the future. - We offer a comprehensive package of benefits including paid time off (vacation, holidays, sick), medical/dental/vision insurance and 401(k) to eligible employees. - This job is eligible to participate in our short-term incentive programs. - This job is eligible to participate in our long-term incentive programs Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of anybonus, commission, incentive, benefits, or any other form of compensation and benefits that are allocable to a particular employee remains in the Company's soleand absolute discretion unless and until paid and may be modified at the Company's sole and absolute discretion, consistent with applicable law. AbbVie is an equal opportunity employer and is committed to operating with integrity, driving innovation, transforming lives and serving our community.  Equal Opportunity Employer/Veterans/Disabled. US & Puerto Rico only - to learn more, visit https://www.abbvie.com/join-us/equal-employment-opportunity-employer.html US & Puerto Rico applicants seeking a reasonable accommodation, click here to learn more: https://www.abbvie.com/join-us/reasonable-accommodations.html

• Design and execute data science experiments such as causal analysis, A/B tests, and offline evaluations to validate product and underwriting decisions. • Develop, evaluate, and iterate on predictive models (e.g., credit/risk scoring, revenue forecasting, policy performance). • Own model performance and monitoring: define success metrics, investigate drift, and drive improvements to data quality and feature reliability. • Partner with Product Engineering to productionize models and analytics, focusing on reliability, reproducibility, and maintainability. • Turn messy real-world data into usable signals through exploratory analysis, feature engineering, and robust validation. • Clearly communicate insights to both technical and non-technical stakeholders through documentation and presentations. • Raise the bar for technical quality via improved analytical standards, code review practices, and documentation. • Mentor and support other team members through pairing, feedback, and sharing best practices.

We are a small team in a big company, adopting agile methodology. We provide Data Science solutions for internal customers inside Deutsche Telekom and our skills and solutions are continually in high demand. Therefore, we want to increase the size of our team with additional technical people that know how to process and analyze data so we can serve and satisfy the needs of even more customers. We are looking for somebody who can work independently, create working solutions quickly, creatively come up with new ideas, but also knows how to use and where to look for existing solutions. Our project members are also situated in Germany, Slovakia, Romania or India so video conferencing is the daily standard. Key Responsibilities - You take the end-to-end responsibility for strategically aligned data science projects, from taking stock of requirements and advising through to putting the solution into production - You will be applying machine learning approaches to provide business insights for internal customers of the Deutsche Telekom group - You will be responsible for driving the discussions within the team for selecting the most appropriate modelling strategies - You will prepare training & evaluation pipelines and apply state of the art Machine Learning approaches to improve processes in Finance (Controlling, Treasury, Accounting), Procurement, HR, and others - You will take part in upskilling fellow Data Scientists - You will be driving innovation by staying up to date with the latest advancements in time series research (e.g., forecasting, clustering, anomaly detection) and identifying their potential applications within our products and projects - We create data-driven business solutions for our customers. You will be the one creating them and possibly deploying them to production, explaining your customers how to use them, and providing support/maintenance - You will be responsible for the technical part in your time series projects designing & implementing prototypes of innovative applications in Python - You will cooperate with the business side including your active contribution in customer workshops, meetings, and calls so the ability to explain technical points to business colleagues is a crucial part of this job, as is a consultant’s mindset - You will participate in team brainstorming sessions, code reviews, or pair programming sessions - Depending on the use case, you will have the opportunity to work with a variety of tools and technologies such as Dagster, Kubernetes, Docker, FastAPI, Redis, Celery and ML frameworks like SKTime, Scikit-learn, Nixtla, Tensorflow or other relevant libraries. - You will have the chance to identify use cases for automation and application of data science Competence Profile - More than 5 years of working experience with Data Science projects, preferably with Time Series forecasting - Profound expertise in time series modelling including areas such as anomaly detection, multivariate forecasting, causal inference and others - Additionally, you have been advising junior Data Scientists in projects - You write clean, comprehensive, and efficient Python code and are an expert in developing machine learning solutions in Python. Additionally, you are familiar with OOP principles, PEP8 guidelines, testing methodologies and API integrations. You are aware of and willing to apply Agile methodology (Scrum, Kanban, etc.) - You have at least basic understanding of SQL that allows you to interact with relational databases and fetch the data from / insert data into them - You are proactive. You do not wait for others to specify what needs to be done, but you take the initiative to identify bottlenecks and areas for possible improvements and you are able to make those work with minimal supervision - You are not afraid to ask questions when something is not clear or point out when something seems inefficient to you - You are an analytical thinker, have an affinity for structure, grasp things fast and work systematically - You can develop working solutions quickly and you get things done - Experience with the basics of DevOps and deployment in cloud environments such as GCP is a plus - Language: Fluent written and spoken English, German skills would be an advantage - Education in the IT field would be beneficial Interpersonal Skills - Proactivity towards customer service is essential - Flexible and responsive to changing work patterns and demands - A thorough and methodical approach to work - Highly developed interpersonal communication skills including storytelling and presentation skills - Knowledge sharing – active contributor

Overview With more than 45,000 employees and partners worldwide, the Customer Experience and Success (CE&S) organization is on a mission to empower customers to accelerate business value through differentiated customer experiences that leverage Microsoft’s products and services, ignited by our people and culture. We drive cross-company alignment and execution, ensuring that we consistently exceed customers’ expectations in every interaction, whether in-product, digital, or human-centered. CE&S is responsible for all up services across the company, including consulting, customer success, and support across Microsoft’s portfolio of solutions and products. Join CE&S and help us accelerate AI transformation for our customers and the world. Within CE&S, the Customer Service & Support (CSS) organization builds trust and confidence for every person and organization through delivering a seamless support experience. In CSS, we are powered by Microsoft’s AI technology to help consumers, businesses, partners, and more, resolve their issues quickly and securely, helping prevent future problems from occurring and achieving more from their Microsoft investment. We are looking for a Senior Data Scientist with to lead high-impact analyses focused on improving the operational efficiency of AI-powered features used by engineers in customer service workflows. This role requires strong expertise in causal inference and econometrics, including methods such as difference-in-differences, regression discontinuity designs, and randomized experiments. What makes this role distinctive is the opportunity to operate at the intersection of causal inference and modern AI systems. The ideal candidate will have familiarity with causal discovery methods (e.g., graphical models, structure learning) as well as experience evaluating LLM outputs along dimensions such as groundedness, robustness, and consistency. You will partner closely with cross-functional teams, including product, and finance, to ensure that both the impact and the quality of AI-driven features are measured, understood, and continuously improved. Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. Responsibilities - Develop and maintain a deep understanding of the end-to-end processes engineers use to resolve customer service cases. - Apply causal inference techniques to estimate the impact of AI-enabled features using observational data; analyze randomized experiments where available; and evaluate the quality of LLM outputs. - Critically assess and benchmark alternative models developed by partner teams, with a focus on both causal impact and output quality. - Extract and transform data using SQL, and build analytical and modeling workflows in Python - Embody our culture and values. Qualifications Required minimum qualifications: - Masters Degree in Mathematics, Analytics, Data Science, Engineering, Computer Science, Business, Economics or related field AND 4+ years experience in data analysis and reporting, data science, business intelligence, or business and financial analysis - OR Bachelors Degree in Statistics, Mathematics, Analytics, Data Science, Engineering, Computer Science, Business, Economics or related field AND 6+ years experience in data analysis and reporting, data science, business intelligence, or business and financial analysis - OR equivalent experience. Preferred Qualifications / Differentiators - Proven track record of using advanced statistical methods to assess the efficiency impact of change on established systems. - Demonstrated ability to understand complex engineering workflows and consistently operate in alignment with organizational culture and values. - Experience applying causal inference methods and experimental analysis to evaluate AI‑enabled features and LLM output quality. - Proficient in SQL for data extraction and Python for building end‑to‑end analytical and modeling workflows. - Ability to assess and build statistical models from very large data sets. Ability to meet Microsoft, customer and / or government security screening requirements are required for this role. These requirements include, but are not limited to the following specialized security screenings: Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud Background Check upon hire / transfer and every two years thereafter. Data Analytics IC5 - The typical base pay range for this role across Canada is CAD $128,000 - CAD $222,400 per year. Find additional pay information here: https://careers.microsoft.com/v2/global/en/canada-pay-information.html Data Analytics IC5 - L'échelle salariale de base typique pour ce rôle dans l'ensemble du Canada est de 128,000 $ CAD à 222,400 $ CAD par année. Pour plus d'information au sujet de la rémunération, veuillez cliquer ici: https://careers.microsoft.com/v2/global/en/canada-pay-information.html Ce poste sera ouvert pendant au moins cinq jours et les candidatures seront acceptées de façon continue jusqu’à ce que le poste soit pourvu. This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled. Microsoft est un employeur offrant l’égalité d’accès à l’emploi. Tous les candidats qualifiés seront pris en considération pour l’emploi, sans égard à l’âge, à l’ascendance, à la citoyenneté, à la couleur, aux congés médicaux ou familiaux, à l’identité ou à l’expression de genre, aux renseignements génétiques, à l’état d’immigration, à l’état matrimonial, à l’état de santé, à l’origine nationale, à un éventuel handicap physique ou mental, à l’affiliation politique, au statut de vétéran protégé ou au statut militaire, à la race, à l’ethnie, à la religion, au sexe (y compris la grossesse), à l’orientation sexuelle ou à toute autre caractéristique protégée par les lois, ordonnances et règlements locaux applicables. Si vous avez besoin d’aide avec des accommodements religieux et/ou d’un accommodement raisonnable en raison d’un handicap pendant le processus de candidature, apprenez-en plus sur la demande d’accommodement. Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.