About Carrot: Carrot is a global, comprehensive fertility and family care platform, supporting members and their families through many of life's most memorable moments. Trusted by many of the world’s leading multinational employers, health plans, and health systems, Carrot’s proven clinical program delivers exceptional outcomes and experiences for members and industry-leading cost-savings for employers. Its award-winning products serve all populations, from preconception care through pregnancy, IVF, male factor infertility, adoption, gestational carrier care, and menopause. Carrot offers localized support in over 170 countries and 25 languages. With a comprehensive program that prioritizes clinical excellence and human-centered care, Carrot supports members and their families through many of the most meaningful moments of their lives. Learn more at get-carrot.com. The Role: We are seeking a Data Scientist to support Carrot’s growing Outcomes Analytics and Growth & Engagement efforts by developing structured, scalable approaches to measuring member engagement, program performance, health outcomes, and revenue impact. This role blends advanced analytics, strategic thinking, and business acumen to inform customer-facing outcomes, drive member engagement, provide pre-sales insights, and assist internal decision-making. This individual will work closely with Clinical Outcomes, Growth & Engagement, Finance, and Carrot’s Enterprise Data Team to connect complex, multi-source data (e.g., product, engagement, marketing, operational, and claims-adjacent data) into defensible measurement frameworks. While not responsible for core data engineering or infrastructure, the role requires strong hands-on experience working with large datasets, leveraging a modern cloud-based analytics stack, and translating analytical findings into clear, actionable insights for senior stakeholders. Key Responsibilities: - Develop and maintain measurement frameworks for engagement, outcomes, and ROI that support customer reporting, pre-sales analytics, and strategic planning - Lead performance and program evaluations, including assessing effectiveness of engagement strategies, clinical programs, and interventions using observational, quasi-experimental, or benchmark-based approaches - Apply predictive analytics, forecasting, and scenario modeling to support growth strategy, customer projections, capacity planning, and network optimization - Conduct ad hoc analyses to answer time-sensitive business, clinical, or customer questions, forming defensible recommendations when data is incomplete or evolving - Serve as an analytics subject matter expert across the member lifecycle—from enrollment and activation through engagement, outcomes, and retention - Analyze member behavior across digital product usage, content engagement, marketing touchpoints, and care pathways to evaluate impact on health outcomes and revenue - Define, monitor, and evolve KPIs and benchmarks aligned with business objectives, including engagement rates, conversion, utilization, and outcomes value - Support forecasting, scenario modeling, and predictive analyses to inform growth strategy, customer projections, and network optimization - Conduct rigorous data quality checks, identify discrepancies, and partner with BI, data science, product, and engineering to improve data reliability and fitness for purpose - Translate complex analytical findings into executive-ready narratives, customer-facing materials, and clear recommendations that can be defended even when data is incomplete - Collaborate cross-functionally to support experimentation, campaign evaluation, and opportunity sizing using behavioral and engagement analytics - Contribute to documentation, knowledge sharing, and mentoring to strengthen analytics best practices across teams What We’re Looking For - Deep experience in advanced analytics, engagement analytics, and outcomes measurement, ideally within healthcare, benefits, or digital health - Strong proficiency working within a modern, cloud-based analytics environment (e.g., SQL, Python/R, dbt, BI tools, data warehouses) - Ability to quickly orient to new data structures, assess data limitations, and build pragmatic, scalable analytical solutions - Comfort forming hypotheses, making recommendations under uncertainty, and balancing rigor with business practicality - Excellent communication skills, with the ability to influence cross-functional partners and senior leaders - A collaborative mindset and curiosity-driven approach to understanding what drives member behavior and how analytics can improve outcomes and revenue Why This Role Matters This is a critical hybrid role that strengthens Carrot’s ability to measure, explain, and scale engagement and outcomes value across customers. By integrating engagement insights with outcomes and financial impact, this role ensures Carrot can confidently tell a cohesive, data-driven story to employers, health plans, and internal stakeholders. As Carrot continues to grow, customers increasingly expect credible, defensible evidence that links member engagement to improved health outcomes, cost savings, and ROI. This role plays a central part in meeting that expectation by developing scalable measurement frameworks, supporting pre-sales and customer reporting, and translating complex data into insights that inform both strategy and execution. Ultimately, this role helps bridge the gap between member behavior, clinical outcomes, and business performance, enabling Carrot to drive smarter decisions, strengthen customer trust, and support long-term growth in a highly competitive and regulated market. The Team: The Outcomes Analytics team is a highly experienced, multidisciplinary group with advanced training in data science, healthcare economics, biostatistics, and related quantitative fields, including Master’s- and PhD-level expertise. The team is responsible for delivering rigorous, decision-ready analytics that support the Growth & Engagement organization by evaluating how new services, benefit designs, and product features influence member engagement, revenue performance, and customer retention. In addition, the team partners closely with Growth & Engagement to assess how campaigns and channels shape member behavior across the lifecycle, including enrollment, utilization, and plan renewal. Minimum Qualifications: - Bachelor’s degree in a quantitative field such as statistics, data science, economics, biostatistics, computer science, marketing analytics, or a related discipline, with 5–7+ years of relevant analytical experience; advanced degree (master’s or Ph.D.) preferred. - Experience in healthcare, health technology, insurance, benefits, or other regulated data environments strongly preferred, including work related to outcomes measurement, utilization analysis, program evaluation, or engagement analytics. - Demonstrated experience designing, evaluating, and interpreting engagement-, utilization-, and outcomes-based models, with a clear understanding of how analytical insights inform financial performance, ROI, and value realization for enterprise, payer, or employer stakeholders. - Strong proficiency working in cloud-based data warehouse environments (e.g., Snowflake, AWS) and with large-scale analytical datasets, including integrating data across multiple systems and domains (e.g., product, engagement, marketing, operational, and outcomes data). - Hands-on experience with analytics engineering approaches such as dbt or warehouse-native pass-through SQL using statistical or analytical tools (e.g., Python, R, SAS), including building, testing, documenting, and maintaining analytical models in collaboration with data engineering and BI teams. - Advanced SQL expertise, with the ability to write efficient, well-structured queries to support complex analytical workflows. - Strong working knowledge of Python for data analysis, including data manipulation, statistical analysis, and applied modeling; experience with R or similar tools is a plus. - Familiarity with advanced analytics, machine learning, and predictive modeling techniques, including regression-based methods, forecasting, cohort analysis, and scenario modeling applied to real-world business or healthcare problems. - Solid foundation in statistical concepts and methods, such as hypothesis testing, regression analysis, experimental or quasi-experimental design, and cohort-based analysis. - Experience analyzing member or customer lifecycle behavior, including conversion funnels, engagement decay, segmentation, response patterns, and personalization strategies, and translating these insights into actionable recommendations. - Experience with marketing and engagement analytics (B2C or B2B2C), including campaign measurement, A/B testing, lifecycle optimization, and evaluation across channels such as email, SMS, search, and in-app experiences. - Proficiency developing clear, decision-ready visualizations and analytical narratives using tools such as Tableau or similar BI platforms, tailored to both technical and non-technical audiences. - Experience following version control and change-management best practices, including Git/GitHub or equivalent approaches in structured analytics environments, to support reproducibility, documentation, and collaborative development. - Proven ability to translate ambiguous business or clinical questions into structured analytical approaches, balancing rigor with practicality when data is incomplete or evolving. - Experience applying best practices in data governance, data modeling, validation, and quality assurance, particularly in environments where analytical outputs must be defensible to external stakeholders. - Strong organizational and prioritization skills, with the ability to manage multiple analytical initiatives in a fast-paced, high-growth environment. - Excellent communication and presentation skills, with the ability to clearly explain analytical findings, assumptions, and limitations to cross-functional partners, including product, growth, finance, clinical, and technical teams. Compensation: Carrot offers a holistic Total Rewards package designed to support our employees in all aspects of their life inside and outside of work, including health and wellness benefits, retirement savings plans, short- and long-term incentives, parental leave, family-forming assistance, and a competitive compensation package. The starting base salary for this position will range from $135,000.00 - $150,000.00. Actual compensation may vary from posted base salary depending on your confirmed job-related skills and experience. Fraud and Security Notice: Please note that all communication regarding job opportunities at Carrot will come exclusively from an @get-carrot.com email address. If you receive messages from any other domain, please disregard them and report the incident to: securityreporting@get-carrot.com Why Carrot? Carrot has received national and international recognition for its pioneering work, including Fast Company's Most Innovative Companies and World Changing Ideas, Inc. Power Partners, and Modern Healthcare’s Innovators. Carrot’s global workforce has been acknowledged with several accolades, including Fortune’s Best Workplaces in Healthcare, Great Place to Work, and Age-Friendly Employer certifications. Carrot is regularly featured in media reporting on issues related to the future of work, women in leadership, and healthcare innovation, including MSNBC, The Economist, Bloomberg, The Wall Street Journal, CNBC, National Public Radio, Harvard Business Review, and more. Learn more at carrotfertility.com.

Data Science Manager East Coast, US Prolific Prolific is not just another player in the AI space—we are the architects of the human data infrastructure that's reshaping the landscape of AI development. In a world where foundational AI technologies are increasingly commoditized, it's the quality and diversity of human-generated data that truly differentiates products and models. The Role Prolific for AI is a high-growth, greenfield vertical building the infrastructure behind human-aligned AI. As Data Science Manager, you'll build and lead the data science and analytics function for this vertical - setting strategy, hiring the team, and partnering with commercial, product, and ops stakeholders to drive measurable impact. You'll define what great looks like, then build the team and systems to deliver it. What you'll be doing Build & Lead the Team - Hire, develop, and retain a high-performing team of Data Scientists and Analysts - Set clear expectations for technical quality — rigorous causal inference, well-designed experiments, principled modelling — and coach the team to meet them - Define ways of working, prioritisation, and how the team interfaces with commercial and product stakeholders Drive Commercial Growth through Data - Ensure your team delivers analytics that fuel the Prolific for AI Sales and Ops functions: pipeline health, forecasting, customer health, and retention signals - Act as a senior data thought partner to commercial leadership — translating business questions into analytical problems and outcomes into decisions Own the Experimentation Standard - Set and hold the bar for how your team designs, runs, and interprets experiments — going beyond basic A/B testing toward rigorous causal inference and algorithmic work - Partner with Product to make experimentation a core capability across the vertical, not just a tool Ensure Data Quality at Scale - Lead your team to build scalable frameworks that guarantee high-quality AI training and evaluation data for Prolific's frontier lab partners - Establish governance: clear rules, repeatable checks, and shared standards that Product and Engineering can build against - Be hands-on in the early phase — contributing technically where needed — then transition to technical oversight and mentorship as the team matures What you'll bring - Proven track record leading data science or analytics teams — you've hired, developed, and held a high technical bar - Technically deep enough to set direction, review work critically, and earn credibility with strong ICs — not just manage process - Expertise in experimentation and causal inference; you know the difference between a well-designed study and a convincing-looking one - Ability to translate ambiguous, high-stakes business problems into structured analytical work - Strong stakeholder influence — you can align Product, Eng, Ops, and Commercial without direct authority - Bonus: experience with AI data pipelines, RLHF, or human-in-the-loop evaluation systems The job spec is a guideline and we are always looking for the best people—we encourage you to apply even if you feel like you don’t meet all the requirements. Why Prolific is a great place to work We've built a unique platform that connects researchers and companies with a global pool of participants, enabling the collection of high-quality, ethically sourced human behavioural data and feedback. This data is the cornerstone of developing more accurate, nuanced, and aligned AI systems. We believe that the next leap in AI capabilities won't come solely from scaling existing models but from integrating diverse human perspectives and behaviors into AI development. By providing this crucial human data infrastructure, Prolific is positioning itself at the forefront of the next wave of AI innovation—one that reflects the breadth and the best of humanity. Working for us will place you at the forefront of AI innovation, providing access to our unique human data platform and opportunities for groundbreaking research. Join us to enjoy a competitive salary, benefits, and remote working within our impactful, mission-driven culture. Links to more information on Prolific Benefits External Handbook Website Youtube Privacy Statement By submitting your application, you agree that Prolific may collect your personal data for recruiting and global organization planning. Prolific's Candidate Privacy Notice explains what personal information Prolific may process, where Prolific may process your personal information, its purposes for processing your personal information, and the rights you can exercise over Prolific use of your personal information.

Job Description Developing statistical, machine learning, and AI models to predict consumer behavior by integrating survey, household, and retail sales data. Leading the design, prototyping, and deployment of AI and machine learning models and algorithms to enhance product and marketing success predictions. Validating and calibrating models and algorithms to estimate the likelihood of success and volume potential of future products, ensuring accuracy and robustness. Automating key processes, developing tools to streamline existing workflows, and ensuring scalability and reproducibility of models. Collaborating with analytics teams to address custom client requests, offering recommendations on complex study designs, and delivering tailored data insights. Staying at the forefront of relevant fields (Statistics, Machine Learning, Operations Research, Marketing Science, Artificial Intelligence), continuously enhancing model performance with the latest techniques. Telecommuting permitted. Qualifications Master’s degree in Marketing Science, Mathematics, Operations Research, Computer Science, Statistics, Financial, and Risk Management, or related and 3 years of experience required. Additional Information This notice is being provided as a result of the filing of a permanent alien labor certification application for this job opportunity. Any person may provide documentary evidence bearing on the application to the Certifying Officer of the Department of Labor: U.S. Department of Labor Employment and Training Administration Office of Foreign Labor Certification 200 Constitution Avenue, NW Room N-5311 Washington, DC 20210 Chicago, IL; 40 hours/week. $119,558.00-$148,500.00/year. This role may be eligible for a sales-based incentive or performance-based bonus. Other benefits include a flexible working environment, comprehensive health insurance, industry-leading parental leave, life insurance, education support, volunteer time off, LinkedIn learning, Employee-Assistance-Program (EAP), and more. APPLY OR QUESTIONS: Any employee with questions about this position may contact [email protected]. Any employee who wishes to apply may submit their resume on NIQ's career page - Careers - NIQ and reference job R26_0006770. If applying, please include a resume. Our Benefits - Flexible working environment - Volunteer time off - LinkedIn Learning - Employee-Assistance-Program (EAP) NIQ may utilize artificial intelligence (AI) tools at various stages of the recruitment process, including résumé screening, candidate assessments, interview scheduling, job matching, communication support, and certain administrative tasks that help streamline workflows. These tools are intended to improve efficiency and support fair and consistent evaluation based on job-related criteria. All use of AI is governed by NIQ’s principles of fairness, transparency, human oversight, and inclusion. Final hiring decisions are made exclusively by humans. NIQ regularly reviews its AI tools to help mitigate bias and ensure compliance with applicable laws and regulations. If you have questions, require accommodations, or wish to request human review were permitted by law, please contact your local HR representative. For more information, please visit NIQ’s AI Safety Policies and Guiding Principles: https://www.nielseniq.com/global/en/ai-safety-policies. About NIQ NIQ is the world’s leading consumer intelligence company, delivering the most complete understanding of consumer buying behavior and revealing new pathways to growth. In 2023, NIQ combined with GfK, bringing together the two industry leaders with unparalleled global reach. With a holistic retail read and the most comprehensive consumer insights—delivered with advanced analytics through state-of-the-art platforms—NIQ delivers the Full View™. NIQ is an Advent International portfolio company with operations in 100+ markets, covering more than 90% of the world’s population. For more information, visit NIQ.com Want to keep up with our latest updates? Follow us on: LinkedIn | Instagram | Twitter | Facebook Our commitment to Diversity, Equity, and Inclusion At NIQ, we are steadfast in our commitment to fostering an inclusive workplace that mirrors the rich diversity of the communities and markets we serve. We believe that embracing a wide range of perspectives drives innovation and excellence. All employment decisions at NIQ are made without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, marital status, veteran status, or any other characteristic protected by applicable laws. We invite individuals who share our dedication to inclusivity and equity to join us in making a meaningful impact. To learn more about our ongoing efforts in diversity and inclusion, please visit the https://nielseniq.com/global/en/news-center/diversity-inclusion - Career Site Team: Technology

OVERVIEW: The Principal Data Scientist position is a senior technical leader who strategizes enterprise-grade AI solutions, spanning agentic AI, NLP, optimization & machine learning, to unlock measurable value across the Supply Chain and aligned domains. By working as a strategic partner to Supply Chain and cross-functional leaders in Product and Engineering, this role translates complex business requirements into rigorously framed analytical problems and robust, production-grade decisioning systems. The Principal Data Scientist shapes and governs the end-to-end AI architecture and strategic roadmap on a variety of AI platforms, ensuring AI capabilities are secure, scalable, and aligned with General Mills technology strategy. They elevate the broader Data Science community through technical mentorship and leadership in AI/ML best practices that accelerate high-quality solution delivery and responsible AI adoption. KEY ACCOUNTABILITIES: - Lead, design, and execute novel, end-to-end AI solutions and systems that help business partners achieve strategic objectives through advanced analytics, modeling, and optimization, with a primary focus on complex Supply Chain decisioning. - Partner with data science leadership, engineering, AI platform teams, and business stakeholders to define, prioritize, and deliver production-grade AI/ML products and services, leveraging best-in-class tools, frameworks, and cloud-native architectures on GCP. - Provide technical leadership through strong business partnership, challenging assumptions, offering alternate architectural patterns, and making informed trade-offs between complexity, performance, cost, and long-term maintainability. - Lead the reference architecture, design, and implementation of LLMs, NLP, and computer vision-driven solutions, owning patterns for problem framing, data curation, model lifecycle, and integration with core enterprise platforms and applications. - Provide technical oversight across core data science methodologies—including statistical, machine learning, and optimization approaches, ensuring method selection, validation, and implementation are rigorous, fit-for-purpose, and consistent with AI standards. - Partner closely with AI Leadership, ML Engineering, and business stakeholders to define and evolve the architecture for agentic AI and retrieval-augmented systems, establishing standards, guardrails, and reusable components. - Own the creation and operationalization of production-ready, scalable AI platforms, services, and models that provide real-time or near-real-time insights and decisions, fully aligned with General Mills technology standards for security, reliability, observability, and lifecycle management. - Provide technical leadership for analytical solution design and experimentation through hypothesis-driven approaches, robust evaluation strategies, and clear error taxonomies, with strong documentation and governance to ensure transparency, reproducibility, and reuse across capabilities. - Serve as a key member of the Data Science leadership team, shaping technical strategy, multi-year capability roadmaps, architectural standards, and operating practices that scale AI impact across the enterprise. - Coach and develop data scientists and adjacent talent through deep technical reviews and mentoring on advanced AI concepts, domain best practices, and effective use of shared platforms and patterns. - Champion Responsible AI by ensuring privacy, security, and governance compliance; proactively identifying and reducing model risks and embedding responsible AI principles into architecture, processes, and user experiences. - Act as an internal and external thought leader on AI strategy, architecture, and data science, representing the Digital and Technology organization in forums, communities of practice, and key stakeholder engagements. MINIMUM QUALIFICATIONS: - 10+ years of experience in data science / applied analytics, with ownership of end-to-end solutions from problem framing through production and measurable business impact with at least 3 years in a Principal, Lead, or equivalent senior technical level. - Advanced degree in a quantitative field (Data Science, Computer Science, Engineering, Statistics, Math, Operations Research, or related). - Strong expertise in core data science methodologies (statistical modeling, machine learning, optimization) and their practical application to complex business problems. - Hands-on experience architecting and deploying scalable AI/ML solutions on a major cloud platform (preferably GCP). - Proven track record of building and operating production-grade models and decisioning systems at scale, including monitoring, performance management, and lifecycle governance. - Demonstrated technical leadership setting technical direction, establishing standards, and influencing architecture and platform decisions. - Experience leading complex AI/ML programs across multiple teams, with strong grasp of project/program management fundamentals (roadmaps, prioritization, risk/dependency management). - Experience with unstructured data and advanced AI (e.g., LLMs, NLP, computer vision) integrated into business workflows and applications. - Strong communication skills, with the ability to clearly explain analytical concepts, results, and trade-offs to both technical and non-technical stakeholders. - Proficiency with modern data science engineering practices: version control, code review, testing, CI/CD for models, and agile delivery. - Demonstrated ability to mentor and develop other data scientists, leading by example on modeling rigor, experimentation, and documentation. - Proven ability to stay current on evolving AI/ML technologies and to anticipate, evaluate, and advocate for appropriate adoption within the enterprise. PREFERRED QUALIFICATIONS: - Deep experience applying data science and AI to Supply Chain domains (e.g., planning, logistics, manufacturing, sourcing). - Experience leading solutions that combine traditional modeling (predictive/prescriptive analytics, optimization) with newer paradigms (LLMs, agentic AI, RAG) in production. - Exposure to large-scale data processing and modern stack components - Evidence of thought leadership in data science (e.g., internal forums, publications, or open-source contributions). ADDITIONAL CONSIDERATIONS: - International relocation or international remote working arrangements (outside of the US) will not be considered. - Applicants for this position must be currently authorized to work in the United States on a full-time basis. General Mills will not sponsor applicants for this position for work visas. Salary Range The salary range for this position is $146900.00 - $245000.00 / Annually. At General Mills we strive for each employee's pay at any point in their career to reflect their experiences performance and skills for their current role. The salary range for this role represents the numerous factors considered in the hiring decisions including, but not limited to, educations, skills, work experience, certifications, etc. As such, pay for the successful candidate(s) could fall anywhere within the stated range. Beyond base salary, General Mills offers a competitive Total Rewards package focusing on your overall well-being. We are proud to offer a foundation of health benefits, retirement and financial wellbeing, time off programs, wellbeing support and perks. Benefits may vary by role, country, region, union status, and other employment status factors. You may also be eligible to participate in an annual incentive program. An incentive award, if any, depends on various factors, including, individual and organizational performance. Reasonable Accommodation Request If you need to request an accommodation during the application or hiring process, please fill out our online accommodations request form by following this link: Accommodations Request.