ROLE SUMMARY Plan and perform care gap advanced analytics and segment HCPs and KOLs using real world data sources as input ROLE RESPONSIBILITIES Strategic support and communications - Support team Product Manager in strategic and tactical planning with regards to medical analyses - Collaborate with team Product manager to communicate generated insights - Provide mentorship & coaching to Data Scientists & Data Engineering - Leverage cross-team collaboration and asset-specific experience to develop and disseminate analytical best-practices in conducing care gap analyses and HCP segmentation - Proactively identify future opportunities, such as data inputs, innovative analytical tools, and capability-building initiatives to enhance the impact and adoption of care gap and segmentation solutions Planning and conducting medical analyses - Prepare and maintain datasets for on-going high-complexity analytical needs , in collaboration with data engineers, including flagging data issues & advising on required solution - Own the end-to-end process of integrated care gaps analyses, including strategic planning, identifying data input required (e.g., claims data for unmet need analysis), and effective visualization / insight generation for users - Plan, generate and perform asset-specific care gap analyses to guide Medical Affairs activities using advanced techniques such as predictive models, machine learning, probabilistic causal models, and unsupervised algorithms - Create asset-specific HCP segments, maps, and prioritizations, across multiple dimensions including care gaps, to guide channel mix/activation, content creation, and MSL activity in Anchor countries BASIC QUALIFICATIONS - Candidate demonstrates a breadth of diverse leadership experiences and capabilities including: the ability to influence and collaborate with peers, develop and coach others, oversee and guide the work of other colleagues to achieve meaningful outcomes and create business impact. - Degree in Data Sciences, or Computer Sciences, Statistics, Clinical Informatics or similar, with advanced qualification in Data Science - Relevant certification &/or work experience in data engineering - Experience (8+ years with Bachelors; 7+ with Masters; 5+ with PHD ) in data sciences, notably in the healthcare sector - Demonstrated ability to independently lead projects & support professional growth of colleagues - Demonstrated effectiveness working in cross-functional business environment. - Proven influencing skills - Strong interpersonal skills to quickly build rapport and credibility with Pfizer leaders and key external stakeholders. - Ability to partner cross culturally/regionally. - Effective English verbal and written communication with flexibility to be clear, consistent, compliant, and appropriate for a variety of settings including scientific/technical, promotional, patient/consumer, regulatory, and media. - In depth understanding of the business of pharmaceutical medicine including clinical trial design, GCP and data interpretation, drug development, regulatory and promotional rules/guidance, legal and compliance, issue management and business development opportunity evaluations. Technical: - Anticipates Customer and Market Needs - Knows the industry; knowledgeable in current and possible future trends, knows the competition; is aware of how strategies and tactics work in the marketplace. Is dedicated to meeting the expectations and requirements of internal and external customer's; always focused on patient safety first, establishes and maintains effective relationships with customers and gains their trust and respect. - Acts Decisively - Makes timely and effective decisions by applying business and financial acumen. Acts with urgency and removes barriers that hinder productivity. Can be counted on to exceed goals successfully; is very bottom-line oriented; steadfastly pushes self and others for results. - Builds Change-Agile Organizations - Develops teams that are facile at initiating and responding to change. Aligns teams and processes to support sustainable change. - Designs and leads teams that are flexible and adaptive. - Strategic and Innovating Thinking - Demonstrates insightful thinking by developing creative approaches to business models and strategies and creates an environment to encourage others to do the same. - Grows Leaders - Actively coaches and develops talent. Builds leadership bench strength for Pfizer. Provides opportunities and experiences to develop skills, competencies, and business knowledge. - Is a role model of Pfizer's values and behaviors. - Demonstrate ability to drive transformational change - Lead teams and engage diverse stakeholders - Understand the applications of technology to the Life Science sector Other Job Details: - Last Date to Apply for Job: April 10th, 2026 - Additional Location Information: New York, NY; Collegeville, PA; Cambridge, MA; Groton, CT; Bothell, WA, Lake Forest, IL; La Jolla, CA; Tampa, FL - Eligible for Relocation Package: No #LI-PFE The annual base salary for this position ranges from $162,900.00 to $271,500.00.* In addition, this position is eligible for participation in Pfizer's Global Performance Plan with a bonus target of 20.0% of the base salary and eligibility to participate in our share based long term incentive program. We offer comprehensive and generous benefits and programs to help our colleagues lead healthy lives and to support each of life's moments. Benefits offered include a 401(k) plan with Pfizer Matching Contributions and an additional Pfizer Retirement Savings Contribution, paid vacation, holiday and personal days, paid caregiver/parental and medical leave, and health benefits to include medical, prescription drug, dental and vision coverage. Learn more at Pfizer Candidate Site - U.S. Benefits | (uscandidates.mypfizerbenefits.com). Pfizer compensation structures and benefit packages are aligned based on the location of hire. The United States salary range provided does not apply to Tampa, FL or any location outside of the United States. * The annual base salary for this position in Tampa, FL ranges from $146,600.00 to $244,400.00. Relocation assistance may be available based on business needs and/or eligibility. Candidates must be authorized to be employed in the U.S. by any employer. U.S. work visa sponsorship (such as TN, O-1, H-1B, etc.) is not available for this role now or in the future. Sunshine Act Pfizer reports payments and other transfers of value to health care providers as required by federal and state transparency laws and implementing regulations. These laws and regulations require Pfizer to provide government agencies with information such as a health care provider's name, address and the type of payments or other value received, generally for public disclosure. Subject to further legal review and statutory or regulatory clarification, which Pfizer intends to pursue, reimbursement of recruiting expenses for licensed physicians may constitute a reportable transfer of value under the federal transparency law commonly known as the Sunshine Act. Therefore, if you are a licensed physician who incurs recruiting expenses as a result of interviewing with Pfizer that we pay or reimburse, your name, address and the amount of payments made currently will be reported to the government. If you have questions regarding this matter, please do not hesitate to contact your Talent Acquisition representative. EEO & Employment Eligibility Pfizer is committed to equal opportunity in the terms and conditions of employment for all employees and job applicants without regard to race, color, religion, sex, sexual orientation, age, gender identity or gender expression, national origin, disability or veteran status. Pfizer also complies with all applicable national, state and local laws governing nondiscrimination in employment as well as work authorization and employment eligibility verification requirements of the Immigration and Nationality Act and IRCA. Pfizer is an E-Verify employer. This position requires permanent work authorization in the United States. Pfizer endeavors to make www.pfizer.com/careers accessible to all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process and/or interviewing, please email disabilityrecruitment@pfizer.com . This is to be used solely for accommodation requests with respect to the accessibility of our website, online application process and/or interviewing. Requests for any other reason will not be returned. Marketing and Market Research

The Opportunity BetterSleep is one of the most downloaded sleep apps in the world, with 85M+ downloads and a global audience of people actively trying to sleep better. We're at an inflection point, moving from a legacy growth model to one built around unit economics, demand quality, and sustainable acquisition. The opportunity: build the growth engine for a brand that millions already use, with startup-level ownership and the resources of a public company. Our team sits at the intersection of consumer product, performance marketing, and data science — and we're building the data foundation to make all three faster and smarter. We run sophisticated UA programs across Facebook, Apple Search Ads, TikTok, and CTV; we run a continuous experimentation program across subscription pricing, onboarding, and content; and we have a growing Firebase + BigQuery data platform that powers it all. We're a lean, high-conviction team and we move fast. The Role We're looking for a Head of Data to own and evolve the entire data function at BetterSleep — platform, people, and strategy. You'll manage a team of data scientists, own the roadmap for our data infrastructure, and serve as the strategic data partner to product, growth, and executive leadership. This is a player-coach role: you'll spend real time in the work — reviewing dbt models, designing data products, unblocking your team — while also setting direction and partnering with the business on the decisions that matter. The data team at BetterSleep was historically weighted toward research and data science. We've been rebuilding it with a platform-first mindset: stable pipelines, reliable definitions, self-service tooling, and governance that makes the whole organization faster. You'll inherit that momentum and lead the next phase of that build. What You’ll Do Data Platform & Engineering - Own the architecture and reliability of the UA data pipeline — BigQuery, dbt, Jenkins, AppsFlyer/SKAN attribution, and our downstream dashboards and Mixpanel warehouse sync - Drive the migration of remaining Python transformation scripts into dbt; establish CI/CD, testing standards, and dev/prod environment hygiene - Partner with engineering on the ingestion layer (ad platform APIs, Firebase, custom subscription backend webhooks) and upstream data quality - Evaluate and introduce new tooling when it's clearly the right call; default to keeping the stack simple Analytics & Measurement - Own the definitions, logic, and reliability of our core metrics: installs, trials, trial-to-paid, RPP, ROAS, CAC, LTV, churn - Lead our attribution methodology — MMP (AppsFlyer), SKAN 4, SSOT deduplication — and translate it clearly to the UA and executive teams - Support our experimentation program: help PMs and the UA team design tests, validate results, and build statistical muscle across the org - Experience building or managing experimentation infrastructure (A/B testing platforms, statistical significance frameworks) - Build self-service data products that reduce the number of ad hoc requests hitting the team — including AI-powered tooling (e.g. natural language querying over Mixpanel/BigQuery, automated anomaly detection, LLM-assisted reporting) where it delivers real leverage Product Analytics - Own product analytics instrumentation strategy in partnership with engineering — event taxonomy, Mixpanel governance, Firebase event schema - Translate product analytics into actionable insight for PMs: retention curves, funnel analysis, feature adoption, onboarding optimization - Ensure the product team can answer their own questions without always needing the data team in the loop People & Partnerships - Manage and develop two data scientists; make hiring decisions around expansion of the team as needed - Partner closely with the UA Manager, Growth PM, and Head of Product as the data team's primary business-facing contact - Set sprint cadence, manage the data backlog, and keep the team focused on high-leverage work Data Governance & AI-Forward Operations - Drive data governance and data semantic layer development; make our visualization platform more usable for non-technical stakeholders - Help the organization identify and automate high-friction internal workflows using AI — this is a company-wide priority with executive sponsorship - Champion a culture of practical AI adoption on the data team and beyond

Please submit your CV in English and indicate your level of English proficiency. Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment. What this opportunity involves  While each project involves unique tasks, contributors may:  - Design original computational data science problems that simulate real-world analytical workflows across industries (telecom, finance, government, e-commerce, healthcare) - Create problems requiring Python programming to solve (using Pandas, Numpy, Scipy, Sklearn, Statsmodels, Matplotlib, Seaborn) - Ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks) - Develop problems requiring non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction - Create deterministic problems with reproducible answers: avoid stochastic elements or require fixed random seeds for exact reproducibility - Base problems on real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency - Design end-to-end problems spanning the complete data science pipeline (data ingestion → cleaning → EDA → modeling → validation → deployment considerations) - Incorporate big data processing scenarios requiring scalable computational approaches - Verify solutions using Python with standard data science libraries and statistical methods - Document problem statements clearly with realistic business contexts and provide verified correct answers What we look for This opportunity is a good fit for Data Science specialists with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:   - 5+ years of hands-on data science experience with proven business impact - Portfolio of completed projects and publications showcasing real-world problem-solving - Expert Python programming for data science (pandas, numpy, scipy, scikit-learn, statsmodels) - Expert statistical analysis and machine learning - deep understanding of algorithms, methods, and their practical applications - Expert with SQL and database operations for data manipulation and analysis - Experience with GenAI technologies (LLMs, RAG, prompt engineering, vector databases) - Understanding of MLOps practices and model deployment workflows - Knowledge of modern frameworks (TensorFlow, PyTorch, LangChain) - Strong written English (C1+). How it works  Apply → Pass qualification(s) → Join a project → Complete tasks → Get paid Project time expectations  For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active.  Compensation On this project, contributors can earn up to $90 per hour equivalent, depending on their level and pace of contribution. Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.

Please submit your CV in English and indicate your level of English proficiency. Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment. What this opportunity involves  While each project involves unique tasks, contributors may:  - Design original computational data science problems that simulate real-world analytical workflows across industries (telecom, finance, government, e-commerce, healthcare) - Create problems requiring Python programming to solve (using Pandas, Numpy, Scipy, Sklearn, Statsmodels, Matplotlib, Seaborn) - Ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks) - Develop problems requiring non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction - Create deterministic problems with reproducible answers: avoid stochastic elements or require fixed random seeds for exact reproducibility - Base problems on real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency - Design end-to-end problems spanning the complete data science pipeline (data ingestion → cleaning → EDA → modeling → validation → deployment considerations) - Incorporate big data processing scenarios requiring scalable computational approaches - Verify solutions using Python with standard data science libraries and statistical methods - Document problem statements clearly with realistic business contexts and provide verified correct answers What we look for This opportunity is a good fit for Data Science specialists with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:   - 5+ years of hands-on data science experience with proven business impact - Portfolio of completed projects and publications showcasing real-world problem-solving - Expert Python programming for data science (pandas, numpy, scipy, scikit-learn, statsmodels) - Expert statistical analysis and machine learning - deep understanding of algorithms, methods, and their practical applications - Expert with SQL and database operations for data manipulation and analysis - Experience with GenAI technologies (LLMs, RAG, prompt engineering, vector databases) - Understanding of MLOps practices and model deployment workflows - Knowledge of modern frameworks (TensorFlow, PyTorch, LangChain) - Strong written English (C1+). How it works  Apply → Pass qualification(s) → Join a project → Complete tasks → Get paid Project time expectations  For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active.  Compensation On this project, contributors can earn up to $90 per hour equivalent, depending on their level and pace of contribution. Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.