Full-Time Vice President of Data Solutions

Develop and execute MDLinx’s data science, engineering, and analytics strategy aligned with business goals for primarily pharma clients.

Build a long-term roadmap for data innovation, advanced analytics, and AI-driven solutions to enhance marketing effectiveness across our platform and suite of products.

Lead data analysis and research as it relates to establishing HCP audience insights and advanced customer journeys.

Champion a culture of data-driven decision-making, influencing both internal teams and external clients.

Lead, mentor, and grow a multidisciplinary team of data scientists, machine learning engineers, data engineers, and analytics professionals.

Foster a collaborative culture that encourages innovation, experimentation, and knowledge sharing across data science, engineering, and analytics functions.

Ensure the MDLinx is equipped with cutting-edge tools, frameworks, and resources to excel.

Lead the full-funnel measurement strategy for omnichannel campaigns, enabling comprehensive tracking and optimization of marketing performance.

Oversee day-to-day analytics and reporting functions at MDLinx, ensuring timely and actionable insights for internal stakeholders and clients.

Design and implement advanced attribution models, such as marketing mix modeling (MMM) and multitouch attribution (MTA), to evaluate and optimize omnichannel efforts.

Drive the design and deployment of machine learning models and AI systems to optimize marketing campaigns, personalize customer experiences, and forecast custom audiences and outcomes.

Develop predictive and prescriptive analytics to support targeting, segmentation, and ROI optimization for pharmaceutical clients.

Innovate in areas such as natural language processing (NLP) for medical content, real-world evidence (RWE) analysis, and patient journey mapping.

Ensure the development and scalability of data infrastructure, pipelines, and platforms to support data science and analytics initiatives.

Implement robust data governance, ensuring security, compliance (e.g., HIPAA, GDPR), and high data quality standards.

Partner with IT and Development teams to maintain seamless integration of data systems with marketing technology platforms.

Build and manage a centralized analytics and reporting function that delivers timely, accurate, and actionable insights to internal teams and clients.

Design intuitive Tableau and other dashboards and reports that empower teams to monitor KPIs such as engagement, conversion rates, and ROI.

Ensure alignment between analytics outputs and broader strategic objectives, supporting both tactical execution and long-term omnichannel engagement planning.

Partner with cross-functional teams, including marketing, product development, and client services, to deliver actionable insights that drive business outcomes.

Collaborate with pharmaceutical clients to understand their challenges and design analytics solutions tailored to their needs.

Act as a bridge between technical teams and executive leadership, translating complex data and analytics concepts into business value.

Define and track KPIs to measure the success of data, analytics, and marketing initiatives.

Deliver impactful presentations and reports to executive leadership, clients, and stakeholders to communicate findings and recommendations.

Minimum Qualifications:

• Master’s or Ph.D. in Data Science, Computer Science, Statistics, Engineering, Marketing Analytics, or a related field.
• 12+ years of experience in data science, analytics, or marketing measurement, with at least 5 years in a leadership role.
• Proven success leading data, analytics, and engineering initiatives in the pharmaceutical, healthcare, or marketing industries.
• Extensive experience with data governance, compliance, and working with sensitive healthcare data.
• Deep knowledge of advanced analytics techniques, machine learning methods, and AI frameworks.
• Expertise in marketing analytics tools such as Google Analytics, Adobe Analytics, Tableau, and Power BI.
• Proficiency in programming languages such as Python, R, and SQL.
• Experience with cloud platforms (AWS, Azure, GCP, Snowflake) and marketing technology ecosystems including DSPs and CDPs like Segment.
• Familiarity with advanced marketing measurement models such as marketing mix modeling (MMM) and multitouch attribution (MTA).
• Experience with real-world evidence (RWE) or clinical data analysis.
• Knowledge of pharmaceutical marketing strategies and key performance metrics.
• Familiarity with omnichannel marketing, customer journey analytics, and campaign optimization in a regulated environment.

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