Job Details
- Lead the design, delivery, and scaling of innovative AI solutions across the organization from pilot phases to full-scale implementation.
- Build and lead a team of data scientists, organizing analytical processes and workflows, and mentoring/developing the managers what work on your team as well as junior team members.
- Drive the delivery process, leveraging agile methodologies and best practices to efficiently progress from pilot projects to scalable solutions, while maintaining a focus on quality and innovation.
- Steer the upgrading and refining capabilities based on feedback and insights gathered during pilot phases, continuously enhancing the effectiveness and relevance of implemented solutions.
- Play a key role in the organizational transformation by championing innovation, fostering a culture of experimentation, and facilitating the adoption of new capabilities at scale.
- Collaborate within the analytics POD, coordinating efforts with the Insight Strategy & Execution and Market Research Insights counterparts to develop and execute AI capabilities a comprehensive brand analytics plan.
- Deliver consolidated insights and actionable recommendations to Commercial teams, ensuring alignment with strategic objectives and insights findings.
- Represent data science function and capabilities in Analytic POD meetings.
- Work closely with cross-functional teams to ensure seamless integration of brand analytics insights into decision-making processes and strategic initiatives.
- Work closely with Analytics Engineering to ensure the data ecosystem is conducive for data science modeling purposes.
- Partner with Digital teams to enhance data science capabilities, aligning efforts to leverage digital data sources effectively.
- Foster collaboration with other teams to ensure seamless integration of data science initiatives across the organization's infrastructure, promoting efficiency and effectiveness in leveraging data for informed decision-making.
Qualifications
- Bachelors degree with 15+ years of experience, preferably in engineering, economics, statistics, computer science, or related quantitative field.
- Advanced degree preferred, with 5+ years of experience in Applied Econometrics, Statistics, Data Mining, Machine Learning, Analytics, Mathematics, Operations Research, Industrial Engineering, or related field preferred.
- Extensive experience using data science models to solve problems in a business environment setting.
- Experience building, managing, and growing high performing & diverse teams across geographies.
Relevant Experience
- Extensive experience with, both traditional SQL and modern NoSQL data stores including SQL, and large-scale distributed systems such as Hadoop and or working in Snowflake/Databricks
- Strong experience with machine learning technology, such as: big data stack, Python, R, and visualization techniques
- Deep understanding of artificial intelligence concepts, experience with AI frameworks and libraries such as TensorFlow or PyTorch is also valuable.
- Experience with influencing commercial strategies and tactics, experience in pharmaceutical or healthcare industry is preferred.
- Extensive experience in management of secondary data with application to real-world data.
- Proven ability to connect, integrate and synthesize analysis and data into a meaningful so what to drive concrete strategic recommendations for brand tactics.
- Skilled of describing relevant caveats in data or in a model and how they relate to business question or recommendation.
- Ability to be flexible, prioritize multiple demands and deal with ambiguity.
PROFESSIONAL CHARACTERISTICS
- Cross-functional influence: Expert in creating strategic direction and velocity through winning and influencing business partners to make complex decisions that influence multiple business areas.
- Growth Mindset: Evaluates, understands, and communicates the impact of certain data insights across the business and works to assist business partners foresee potential strategic changes.
- Analytical Thinker: Understands how to synthesize facts and information from varied data sources, both new and pre-existing, into discernable insights and perspectives; takes a problem-solving approach by connecting analytical thinking with an understanding of business drivers.
- Strong Data and Information Manager: Understands and uses analytical skills/tools to produce data in a clean, organized way to drive objective insights.
- Exceptional Communicator: Can understand, translate, distill and present the complex, technical findings of the data science team into commentary that facilitates effective decision making; can readily align interpersonal style with the individual needs of others.
- Thought Partnership: Brings forward recommendations/questions that influences stakeholders; builds robust and long-term strategic relationships with individuals from all levels of the organization, understanding individual goals and objectives to ensure future alignment.
- Highly Collaborative: Manages projects with and through others; shares responsibility and credit; develops self and others through teamwork.
- Strong Project Manager: Clearly articulates scope and deliverables of projects; breaks complex initiatives into detailed component parts and sequences actions appropriately; develops action plans and monitors progress independently; designs success criteria and uses them to track outcomes; drives implementation of recommendations when appropriate, engages with stakeholders throughout to ensure buy-in.
- Proactive Self-Starter: Takes an active role in ones own professional development; stays abreast of analytical trends, and cutting-edge applications of data.