Hiring company: Takeda
Role Overview:
The Associate Director, Data Scientist (Digital & Omni-channel Marketing) is responsible for using data analytics to optimize the delivery of key information to HCPs to support better patient outcomes. The Data Scientist will be a central member of the Data Science Team in US Commercial Operations, a unique center of excellence that partners across Takeda’s US Business Unit to tackle critical, challenging & cross-cutting business questions, with a focus on patient & digital/omni-channel analytics, by developing analytical solutions that drive actionable business strategies. The Associate Director, Data Scientist (Digital & Omni-channel Marketing) will:
- Leverage their experience in healthcare and marketing analytics to develop new analytical approaches to enable partners in sales and marketing to optimize the delivery of key information to HCPs with maximal impact.
- Develop analytical models based on big, rich & complex pharma data sets to enable marketing strategies that refine message targeting, content, timing, sequencing, channel, etc. personalized to individual customers.
- Use a scientific approach to dissect complex business questions, understand causal relationships using data, develop specific hypotheses that inform actionable strategies.
- Drive execution by taking an agile approach to implement strategies in the field, leveraging pilots to measure impact, test hypotheses and refine strategies.
- Translate the results of complex analyses into clear, actionable insights & field execution strategies, and present these to stakeholders and non-technical leadership to gain buy-in and partnership required to fully deliver the solution (end-to-end)
- Collaborate with internal and external stakeholders including brand, sales, marketing, field and others to ensure the approach is tailored to the specific business needs and question.
This role is a unique opportunity to leverage a combination of business, pharma, marketing & data science experience to make a significant impact on patients. More specifically, many rare disease patients endure a years-long journey before receiving an accurate diagnosis & appropriate treatment because of the challenge for HCPs to “connect the dots” and recognize the link between their symptoms and the underlying rare disease. By optimizing the delivery of key info on diseases & treatment options to HCPs (goal: deliver the right info, at the right time, for the right HCP, treating the right patients), the Associate Director, Data Scientist will directly impact patient outcomes by supporting faster diagnosis, treatment & improved access to life-changing therapies.
Role Details:
Objectives/Purpose:
- The main responsibility of the Data Scientist position is to tackle key business questions related to sales & marketing from across the US Business Unit by developing novel analytical capabilities that, at the highest-level, synthesize clear & actionable insights from big, rich & complex data on patients & HCPs and their journeys.
- The Data Scientist will partner with stakeholders, leadership and the Lead Data Scientist to identify marketing business questions to address, design appropriate solutions and support their execution in the field, for therapeutic areas ranging from rare (100s or 1000s of patients) to other markets with with millions of patients.
- The Data Scientist will take a scientific approach to dissecting the business question at hand, curiously investigating the breadth of patient, business and market factors relevant to it.
- The Data Scientist will draw on their healthcare and pharma experience, along with creativity, technical expertise and business acumen to devise innovative solutions that leverage statistical models to integrate data on multiple facets of the healthcare ecosystem into fully contextualized analyses of the factors that affect treatment decisions.
- The Data Scientist will further leverage their experience in marketing analytics to develop strategies to pull insights through to optimize the targeting and delivery of information to the right customers at the most opportune time. This will include optimizing the message, timing, channel of delivery and other aspects to maximize the impact of the information to drive improved patient outcomes.
- The Data Scientist will develop strategies to test the effectiveness of novel tactics, and perform analytics to identify opportunities to itteratively-refine the approach.
- The Data Scientist will work to distill clear, actionable insights from the complexity of their analysis and data, communicating to stakeholders and leadership the key insights and implications of their work without obfuscatory technical detail.
- Finally, the Data Scientist will enable their efforts to be supported, reused or expanded upon by managing the various stages of technical development including promoting proof-of-concept code into production.
Accountabilities:
- Leverage their experience in healthcare and marketing analytics to develop new analytical approaches to enable partners in sales and marketing to optimize the delivery of key information to HCPs with maximal impact.
- Lead the development of novel marketing analytics capabilities, including both the high-level approach, the technical & statistical implementation, field execution, and subsequent optimization via testing (e.g., AB testing), measuring impact, & refinement of the solution.
- Use problem solving methodologies and data science expertise to propose creative analytical solutions to business problems. Take a scientific approach to dissecting complex business questions.
- Collaborate with internal and external stakeholders including brand, sales, marketing, field and others to ensure the approach is tailored to the specific business needs and question.
- Translate the results of complex analyses into clear, actionable insights & field execution strategies, and present these to stakeholders and non-technical leadership to gain buying and partnership required to fully deliver the solution (end-to-end)
- Design and manage complex analytical projects, including developing and implementing approaches that breakdown complex problems into multiple independent & sequential phases of analysis
- Develop, validate and deploy predictive and diagnostic solutions using reusable code and computing paradigms; serve as a technical expert to coach, and review code for other data scientists and external partners
- Process and analyze large health-related datasets ranging from small to Big Data and integrate and analyze Structured, Semi-structured, and Unstructured data
- Lead the development of statistical models, especially interpretable regression-type models, to quantify the effect and interaction of many different factors that affect patients’ and their healthcare journeys. Identify problems that would benefit from more advanced ML methodologies, and lead their implementation.
- Act as both an individual contributor and project team lead for the development of complex but maintainable script pipelines in the R language &/or Python. Use packages such as tidyr to efficiently manipulate data and ggplot2 for visualization (as examples).
- Supervise the promotion of projects and code pipelines from pilot analysis to production-ready code, and finally to ongoing support of in-production workflows. Ensure code pipelines are well-documented, reproducible and maintainable.
Competencies & Skills:
- Experience with pharmaceutical & marketing/omni-channel data and analytics, including the development of new marketing strategies/tactics based on data-driven insights and experience deploying, supporting & optimizing these solutions in the field.
- Excellent stakeholder management & communication skills, especially in the context of complex cross-functional collaborations spanning analytics, marketing and field teams.
- Proven ability and training in generating advanced insight from statistical models, including (but not limited to) multivariate linear regression, cluster algorithms, decision trees, logistic regression, Principal Component Analysis (PCA), time series, survival analysis, machine learning (supervised and unsupervised), Bayesian Methods, Neural Networks, etc.
- Demonstrated proficiency with statistical computing, scripting, data pipelining and numerical analysis
- Experience with using software development principles to develop maintainable, reproducible and expandable code. Experience with source control such as git.
- Proficiency in bringing structure to ambiguous problems and deriving insights from multiple data and information sources
- Ability to develop frameworks for steering complex analytics projects.
- Strong analytical thinker with an abundance of intellectual curiosity
- Excellent interpersonal & communication skills, with strong customer focus and the ability to build strong relationships and networks across the organization and externally
- Experience in pharma and the healthcare industry. Knowledge of the prescription drug distribution process in a large healthcare organization, or prescription drug vendor is a plus.
- Ability to lead and coach other team members or partners with similar skill set, formally or informally.
Education & Experience:
Required:
- Bachelor’s Degree in a technical, quantitative or scientific discipline. For example, Statistics, Analytics, Data Science, Mathematics, Systems Biology, Biophysics, Econometrics, Operations Research or other STEM field.
- 6 years of progressive experience in complex analytical projects including advanced data analysis and statistical modeling. Total experience can be drawn from advanced academic (Master’s, PhD and/or post-doc), research and/or professional/industry setting.
- Experience in both pharmaceutical & marketing/omni-channel analytics required. Demonstrated success in developing & executing on solutions derived from analytics and pulled-through to deployment (e.g., into the field).
- Demonstrated experience leading the development of complex, multi-staged analyses in a creative way from conception, to technical approach, to a satisfactory conclusion
- Extensive hands-on experience with statistical computing, data manipulation, exploratory data analysis, data visualization, statistical modeling, regression-type analysis, model interpretation
- Expertise in developing complex analyses in the R programming language, including both base and modern packages (e.g., tidyr, ggplot2). Python experience is also a plus.
Desired:
- Master’s or PhD in highly technical/quantitative discipline, for example Statistics, Analytics, Data Science, Mathematics, Systems Biology, Biophysics, Econometrics, Operations Research or other STEM field strongly preferred
- 3+ years in a professional analytical role
- 2+ years in professional pharmaceutical / biotechnology / healthcare industry with a focus on pharma marketing analytics (e.g., digital, omni-channel) preferred
COVID UPDATE: Effective November 1, 2021, absent an approved religious or medical reason, all US office-based and lab-based Takeda employees who work fully on-site or in a hybrid model (as determined by Takeda) must be fully vaccinated to work at a Takeda site or to engage with Takeda colleagues or anyone else on behalf of Takeda. As of the same date, absent an approved religious or medical reason, US field-based employees, employees must be fully vaccinated in order to continue in their current roles. US employees who work at a Takeda manufacturing facility, and those who work at a BioLife center or BioLife lab, may be subject to different guidelines. Candidates are encouraged to speak with their recruiter to seek further information on the applicable guidelines for the Business Unit/Function for which they have applied.
EEO Statement
Takeda is proud in its commitment to creating a diverse workforce and providing equal employment opportunities to all employees and applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, gender expression, parental status, national origin, age, disability, citizenship status, genetic information or characteristics, marital status, status as a Vietnam era veteran, special disabled veteran, or other protected veteran in accordance with applicable federal, state and local laws, and any other characteristic protected by law.