The Lead, Data Sciences Strategy and Applications, occupies a vital leadership position within the Office of Data Sciences at the Abigail Wexner Research Institute. This role demands a visionary leader with extensive experience in software development for data sciences applications, focusing on bioinformatics, computational genomics, data visualization, and leveraging big data in biomedical health sciences research. The successful candidate will lead a team in developing sophisticated data solutions that incorporate machine learning, advanced language models, statistical analysis, and data visualization techniques to address the complex challenges of biomedical data science.

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What You'll Do:

Lead a team of software engineers and data scientists through the entire data science project lifecycle, focusing on generative AI, large language models (LLMs), and machine learning (ML) projects from data collection and preprocessing to analysis, modeling, and deployment.
• Collaborate effectively with research and clinical faculty and staff to deliver impactful data science applications, facilitating advanced analysis of diverse medical datasets and supporting the adoption of these applications in research and clinical settings.
• Lead and mentor a diverse team of software engineers, bioinformatics scientists, and data scientists in the development of innovative data science solutions.
• Spearhead research into emerging data science methodologies, including transformative AI, autoML, and big data analysis, ensuring the adoption of best practices and cutting-edge technologies.
• Drive the strategic integration of genomic data with clinical insights, enhancing research capabilities and operational efficiency.
• Foster collaboration across research teams and stakeholders, guiding data science projects from conception to deployment.

• Bachelor of Science (B.S.) degree in Computer Science, Data Science, or a closely related field with at least 10+ years of professional experience (15 preferred).
• Expertise: Software Engineering Excellence: Demonstrated expertise as a software engineer, showcasing a comprehensive ability to lead software application projects from their conceptualization to full-scale production. Proficient in Apache Spark, Python, and Java, with a history of successful project delivery.
• Computational Genomics Proficiency: A minimum of 5 years dedicated to computational genomics, complemented by an in-depth understanding of bioinformatics and genomic data analysis. This includes practical experience in handling, analyzing, and deriving insights from complex genomic datasets.
• Data Architecture Expertise: Advanced knowledge in the design and management of Data Lakes and Data Warehousing, enabling the efficient storage, retrieval, and analysis of vast quantities of both raw and structured data. These skills are critical for optimizing data for accessibility and insightful querying.
• Cloud Computing Specialization: Expert-level proficiency in AWS Cloud Computing, with a focus on serverless architectures, AWS EMR, and familiarity with additional AWS services that enhance data processing and analysis capabilities.
• Artificial Intelligence and Machine Learning: Experience in Artificial Intelligence, including generative AI and Large Language Models (LLMs), as well as Machine Learning techniques. Proficiency in programming and analytics tools such as Python, R, TensorFlow, and PyTorch is essential for developing and deploying advanced AI and ML models.
• Research and Scholarship: Extensive experience in research, with a history of authoring publications and presenting findings at conferences or industry events. This reflects a candidate's ability to contribute to the scientific community and stay at the forefront of data science innovation.
• Qualities: Project Management: Proven capability to manage multiple projects simultaneously, adapting to dynamic priorities with agility and ensuring successful outcomes.
• Communication and Interpersonal Skills: Exceptional attention to detail paired with superior communication and interpersonal skills, facilitating effective collaboration and knowledge sharing across multidisciplinary teams.
• Problem-Solving and Creativity: A creative and analytical approach to problem-solving, bolstered by strong project management abilities. Ability to navigate complex challenges and deliver innovative solutions.
• Leadership and Team Development: Demonstrated leadership experience in guiding, mentoring, and expanding data science teams. A track record of fostering professional growth and building cohesive, high-performing teams.
• Ethical AI Commitment: A deep commitment to continuous learning with a focus on ethical AI practices, ensuring the responsible development and application of technology.
• The above list of duties is intended to describe the general nature and level of work performed by individuals assigned to this classification. It is not to be construed as an exhaustive list of duties performed by the individual so classified, nor is it intended to limit or modify the right of any supervisor to assign, direct, and control the work of employees under his/her supervision.
• EOE M/F/Disability/Vet