Job Description

Support the early Oncology clinical drug research and development process by providing strategic planning and execution, including clinical trial design and all aspects of descriptive, diagnostic, predictive and prescriptive analytics of data related to clinical projects like actual trial data, registries and real-world data bases. Represent biostatistics and coordinate the inputs from programing and data management at a substance/asset level regarding data science related aspects. Collaborate with cross-functional teams to design, evaluate, and optimize clinical trial strategies and development scenarios. As an employee of Boehringer Ingelheim, you will actively contribute to the discovery, development and delivery of our products to our patients and customers. Our global presence provides opportunity for all employees to collaborate internationally, offering visibility and opportunity to directly contribute to the companies' success. We realize that our strength and competitive advantage lie with our people. We support our employees in a number of ways to foster a healthy working environment, meaningful work, mobility, networking and work-life balance. Our competitive compensation and benefit programs reflect Boehringer Ingelheim's high regard for our employees.

Duties & Responsibilities:

• Lead and oversee designing, transforming, analyzing and reporting complex early Oncology clinical trials or projects with established BI experience .
• Lead and oversee for designing, transforming, analyzing and reporting of other data from research and development like registries and real-world data bases with respect to a specific use case or project/asset.
• Develop and implement fit-for-purpose statistical designs and Go/NoGo decision frameworks through simulations and scenario planning to ensure high-quality evidence generation.
• Keep abreast of data science within and outside BI. Apply advanced statistical methodologies and turn derived insights into new data science approaches for early Oncology clinical development.
• Support fostering innovative digital approaches to produce sophisticated, intelligent optimization solutions, innovative processes and predictive models.
• Present compelling validated stories regarding complex data science aspects to Biostatistics colleagues and other professionals within and outside of BI.
• If applicable, supports the clinical drug development process up to the level of substance/assets.
• Guide and/or lead other colleagues, internal and external customer and external providers on data science related tasks.
• Coordinate cross-functional working with programming and data management.
• Be a team player and contribute to cross-functional collaborations.
• Supports regulatory interactions by ensuring statistical rigor in evidence strategies.
• Participate in cross-functional BI internal working-groups and drive/plan relevant data science aspects. Participate in external working groups.
• Liaise with late phase Oncology Biostatistics and Data Science team to leverage synergies and share knowledge

Senior Associate Director level only:

• Subject Matter Expert (SME) / Process Lead for designing, transforming, analyzing and reporting complex early Oncology clinical trials or projects, that represent new challenges and for which project and therapeutic knowledge is not given.
• Subject Matter Expert (SME) / Process Lead for designing as well as transforming, analyzing and reporting of other data that represent new challenges from research and development like registries and real-world databases.
• Identify trends in data science within and outside BI.
• Lead cross-functional BI internal working-groups and drive/plan relevant data science aspects.
• Foster innovative digital approaches to produce sophisticated, intelligent optimization solutions, innovative processes and predictive models.
• If applicable, supports the clinical drug development process up to the level of Therapeutic Area/assets.

Requirements:

• Bachelor of Science (BSc) from an accredited institution in Statistics, Mathematics, Computer Science or related field (Psychology, Data Science, Finance, etc.), with a minimum seven (7) years of data science experience; Or
• Master of Science (MSc) from an accredited institution in Statistics, Mathematics, Computer Science or related field (Psychology, Data Science, Finance, etc.), with six (6) years of experience within the pharmaceutical industry, CROs, regulatory authorities or academic institutions; Or
• Doctoral Degree (PhD) from an accredited institution in Statistics, Mathematics, Computer Science or related field (Psychology, Data Science, Finance, etc.), with three (3) years of experience within the pharmaceutical industry, CROs, regulatory authorities or academic institutions.
• Working experience might be partially compensated by broad and deep topic-specific knowledge.
• Broad knowledge and advanced experience in software languages relevant for business needs.
• Broad knowledge and advanced experience in understanding of clinical trial development process required.
• Advanced project lead experience required.
• Understanding and applying key of principles of data science.
• In-depth understanding of advanced statistical concepts related to Data Science.
• Demonstrated broad knowledge in planning, transforming, analyzing, interpreting, and reporting data in complex clinical trials, in projects with established BI experience or data from other sources in clinical research and development.
• Thorough knowledge of statistical methodology, design of clinical trials or clinical experiments, basic medical terminology and on processing clinical trial information.
• Advanced working knowledge of broad variety of aspects of relevant software languages.
• Mindful of local, global, internal and external cultures to ensure that messages are received positively and effectively.
• Ability to lead and facilitate meetings.
• Ability to develop and deliver training related to data science topics.
• Evidence of strong teamwork, also in global and remote context.
• Good interpersonal skills with the ability to interact effectively with people, internally and externally (e.g. CROs, experts, management).
• Ability to pro-actively identify issues and solutions and to interact with internal and external bodies on routine data science issues.
• Language skills: English: fluent (Read/Write/Speak).
• Know, understand, and implement:

Senior Associate Director level only:

• Bachelor of Science (BSc) from an accredited institution in Statistics, Mathematics, Computer Science or related field (Psychology, Data Science, Finance, etc.), with a minimum of ten (10) years of data science experience; Or
• Master of Science (MSc) from an accredited institution in Statistics, Mathematics, Computer Science or related field (Psychology, Data Science, Finance, etc.), with ten (10) years of experience within the pharmaceutical industry, CROs, regulatory authorities or academic institutions; Or
• Doctoral Degree (PhD) from an accredited institution in Statistics, Mathematics, Computer Science or related field (Psychology, Data Science, Finance, etc.), with six (6) years of experience within the pharmaceutical industry, CROs, regulatory authorities or academic institutions.
• Working experience might be partially compensated by broad and deep topic-specific knowledge.
• Comprehensive knowledge and advanced experience in software languages relevant for business needs.
• Comprehensive knowledge and advanced experience in understanding of clinical trial development process required.
• Broad knowledge and advanced project lead experience required.
• Demonstrated comprehensive knowledge in planning, transforming, analyzing, interpreting, and reporting data in complex situations that represent new challenges and for which project and therapeutic knowledge is not given.
• Excellent knowledge of statistical methodology, design of clinical trials or clinical experiments, basic medical terminology and on processing clinical trial information.
• Advanced understanding of cutting-edge statistical concepts related to Data Science.
• Comprehensive working knowledge of broad variety of aspects of relevant software languages.

Preferred Qualifications:

• Basic medical understanding of Oncology disease areas, including familiarity with clinical endpoints, RECIST criteria, cancer-related terminology, and therapeutic strategies.
• Familiarity with Oncology translational endpoints (e.g., exploratory or early surrogate markers) and statistical modeling for translational research.