About Us:

The Applied Data Science Center (ADSC) is an organization dedicated to improving patient lives by providing data science solutions that help clients increase trial success, shorten development timelines, and reduce costs in bringing new drugs to market. Our vision is to become an essential resource for life science professionals, who rely on our machine-learning solutions to inform strategic decisions and accelerate operations in the drug development lifecycle.

Our core values include:

Ownership & Accountability: We encourage each member of our team to take responsibility for their work and demonstrate leadership, initiative, and commitment. We empower our team members to collaborate effectively and deliver meaningful results that contribute to the success of our clients and the organization.

Entrepreneurship & Innovation: We believe in the power of creative problem-solving and embrace opportunities to explore and develop lean-agile, disruptive solutions in collaboration with our IQVIA colleagues, customers, and users. Our innovative mindset drives us to constantly seek new ways to support our clients in their drug development efforts.

Intellectual Curiosity & Continuous Improvement: Our team is driven by a desire to continuously grow and expand our knowledge and understanding of both the business and technical aspects of our work. We believe that this curiosity is critical to our success, and we are committed to constantly improving our services, supporting our clients and users, and developing ourselves as professionals.

High-Performance Culture: We strive to build a cohesive team that works together towards a common goal. We achieve this through clear communication, fostering trust and psychological safety, and ensuring a healthy work-life balance for all team members.

By adhering to these values, we aim to revolutionize the drug development process and make a lasting, positive impact on the lives of patients worldwide.

Job Description:

The VP, Machine Learning is a visionary individual responsible for identifying, piloting, and productizing data science and machine learning solutions within the IQVIA Research and Development Solutions (RDS) organization. With a strong technical background and customer-facing expertise, this leader manages interdisciplinary teams and collaborates with stakeholders across the industry to revolutionize drug development and improve patient outcomes. The ideal candidate holds an advanced degree in data sciences or computer sciences and has extensive experience leading machine learning teams within the pharmaceutical sector. As a passionate advocate for innovation, the leader inspires and drives the organization toward embracing new ways of working and leveraging cutting-edge technology to make a lasting, positive impact in the field of drug development.

Responsibilities:

The VP, Machine Learning plays a crucial role in driving innovation and growth within the organization and across the broader IQVIA Research and Development Solutions (RDS) ecosystem, Key responsibilities of this role include:

• Development and execution of ML investment priorities, including GenAI program
  • Identifying, piloting, and productizing data science and machine learning solutions to enhance the capabilities of the RDS organization, in collaboration with key stakeholders and business leaders
  • Working with key stakeholders, product managers, and engineering team leads to manage and execute against an investment portfolio to fund strategic initiatives and drive growth

• Growth of the R&D ML business
  • Growing market-facing machine learning and data science offerings as leading solutions in the industry.
  • Leading a team of market-facing AI consultants who work closely with clients to identify their needs and provide tailored solutions.
  • Working closely with the aligned sales team to achieve revenue objectives
  • Oversight and growth of P&L of the business unit

• Thought leadership, change management, and ML adoption
  • Regularly presenting to customers on innovation and machine learning within R&D, showcasing IQVIA’s thought leadership and expertise.
  • Serving as the chief advocate for change and positive disruption of R&D through AI, inspiring others to embrace innovation and new ways of thinking.
  • Actively contributing to thought leadership in the field of AI and machine learning, positioning IQVIA as industry leaders.
  • Understanding and applying the dynamic global regulatory authority ML regulations and requirements, as well as helping to shape the regulatory guidelines

• Management of the Machine Learning team
  • Overseeing the ML architecture and engineering team, ensuring the delivery of high-quality, innovative AI solutions.
  • Managing team and relevant investment budget, ensuring efficient allocation of resources and effective project management.
  • Collaborating with other technology departments across RDS and IQVIA to foster cross-functional innovation and knowledge sharing.

By fulfilling these responsibilities, the VP, Machine Learning plays a pivotal role in shaping the future of drug development and improving patient outcomes through the power of AI and data-driven insights.

Qualifications:

The ideal candidate for the VP, Machine Learning should possess a unique combination of skills and experience that enable them to excel in this critical role. Key qualifications include:

• Advanced degree: The candidate should hold an advanced degree in mathematical or computer sciences, ensuring a strong foundation in the theoretical and practical aspects of machine learning and data science.
• Extensive experience: The candidate should have at least 10 years of experience leading ML teams, demonstrating a successful track record of managing complex projects and delivering innovative solutions.
• Industry knowledge: The candidate should possess a deep understanding of the machine learning landscape within the pharmaceutical industry, ensuring their ability to identify relevant opportunities and navigate challenges unique to this sector.
• Customer-facing and sales growth expertise: The candidate should have a strong background in working with clients, showcasing excellent communication and interpersonal skills, and the ability to understand and address their needs effectively.
• Technical proficiency: The candidate should have a robust technical background, including experience in ML architecture, engineering, and application development.
• Academic publications: While not required, having academic publications in the field of machine learning or related areas would be a significant plus, showcasing the candidate's thought leadership and expertise.
• Passion for innovation: The candidate must be able to passionately advocate for new ways of working, inspiring others to embrace change and adopt innovative approaches to problem-solving.
• P&L expertise: Driving and growing a business unit or individual offerings

By possessing these qualifications, the VP, Machine Learning will be well-equipped to drive innovation, growth, and positive disruption within the organization, ultimately contributing to the advancement of drug development and the betterment of patient outcomes through AI and data-driven insights.

IQVIA is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

IQVIA is a leading global provider of advanced analytics, technology solutions and clinical research services to the life sciences industry. We believe in pushing the boundaries of human science and data science to make the biggest impact possible – to help our customers create a healthier world. Learn more at https://jobs.iqvia.com

We are committed to providing equal employment opportunities for all, including veterans and candidates with disabilities. https://jobs.iqvia.com/eoe

IQVIA’s ability to operate and provide certain services to customers and partners necessitates IQVIA and its employees meet specific requirements regarding COVID-19 vaccination status. https://jobs.iqvia.com/covid-19-vaccine-status

The potential base pay range for this role, when annualized, is $222,000.00 - $378,000.00. The actual base pay offered may vary based on a number of factors including job-related qualifications such as knowledge, skills, education, and experience; location; and/or schedule (full or part-time). Dependent on the position offered, incentive plans, bonuses, and/or other forms of compensation may be offered, in addition to a range of health and welfare and/or other benefits.