Role Description This role offers a unique opportunity to lead advanced data science initiatives in the manufacturing domain, driving measurable improvements across production, operations, and supply chain processes. You will work on end-to-end data solutions, from integrating industrial systems and extracting real-time data to building predictive models and delivering actionable insights. The position blends hands-on engineering with strategic problem solving, allowing you to influence operational efficiency and decision-making at scale. Ideal candidates are skilled in cloud-based data pipelines, machine learning, and industrial protocols, and can communicate complex analyses effectively to both technical teams and executive stakeholders. You will collaborate across remote, global teams in a dynamic, innovative environment that values impact, learning, and cross-functional expertise. - Lead the development and deployment of predictive models for maintenance, anomaly detection, demand forecasting, and process optimization in manufacturing settings - Build and optimize scalable cloud data pipelines for high-volume IoT and operational data using tools like Spark, Kafka, Airflow, and Delta Lake - Integrate OT and IT systems including MES, SCADA, and ERP for real-time data extraction and analysis using industrial protocols such as OPC-UA, MQTT, and Modbus - Apply statistical methods, Six Sigma, SPC, OEE, and lean methodologies to drive measurable gains in yield, uptime, and efficiency - Translate complex model outputs into actionable insights and recommendations for operations and executive stakeholders - Design and execute experiments and simulations to validate process improvements and quantify business impact - Collaborate with cross-functional teams to ensure solutions align with business objectives and operational realities Qualifications - 8–10 years of overall data science experience with 2–4 years in the manufacturing domain - Strong proficiency in SQL and Python, with hands-on experience in medallion/lakehouse architectures on platforms like Databricks, Snowflake, AWS, or Azure - Proven experience in building, deploying, and operationalizing ML models in industrial environments using scikit-learn, TensorFlow, or PyTorch - Deep understanding of industrial operations, production planning, and systems (MES, SCADA, ERP) - Expertise in data engineering, cloud data pipelines, and IoT data integration - Solid grounding in statistical methods: time series analysis, regression, clustering, hypothesis testing - Strong communication skills with the ability to convey technical insights to non-technical stakeholders - Experience designing A/B experiments and process simulations to evaluate business impact - Adaptable, collaborative, and capable of working in a fast-paced, remote, and cross-functional environment Benefits - Opportunity to work on cutting-edge data science projects in manufacturing and industrial operations - Remote work with occasional travel across the United States - Exposure to high-impact, enterprise-scale industrial data environments - Collaborative, innovative, and non-hierarchical work culture - Professional growth opportunities through hands-on experience with advanced ML and data engineering - Competitive contract-to-hire compensation

Role Description The Computer Scientist (Journeyman) supports the research, design, and development of software-based analytical solutions. This role focuses on applying computer and information science principles to solve complex data, modeling, or system challenges. Qualifications - Bachelor’s degree (BA/BS) in Computer Science or a related field - 3–15 years of professional experience in software development, systems engineering, or applied computer science Requirements - U.S. citizenship - Ability to obtain and maintain a Tier 3 investigation - Experience working in secure or regulated environments preferred Benefits - Health insurance - Dental insurance - Vision insurance - Life Insurance - 401(k) Retirement Plan with matching - Paid Time Off - Paid Federal Holidays

Role Description Quanticate is seeking an experienced Clinical Data Project Manager to lead and manage complex data management projects across the clinical development lifecycle. This is your opportunity to bring strategic insight and operational leadership to a role that directly supports the success of our global pharmaceutical and biotech partners. As a Clinical Data Project Manager at Quanticate, you’ll take ownership of high-value clinical data projects, driving delivery excellence and regulatory compliance from start to finish. If you thrive on leadership, precision, and strategic impact, we want to hear from you. - Lead full lifecycle project management from data setup to database lock - Ensure successful delivery of CDM activities to time, budget, and regulatory standards (ICH-GCP) - Act as the primary liaison for clients—managing communication, escalations, and expectations - Drive operational excellence, process consistency, and team productivity across global CDM projects - Manage budgets, scope changes, risk mitigation, and resource allocation - Represent Quanticate at client meetings, audits, and conferences - Assist on bid defences with clients Qualifications - Degree in Life Sciences or similar (or equivalent experience) - Strong experience in Clinical Data Management, including CRO experience - Demonstrated success in leading complex global CDM projects - Deep knowledge of EDC systems (e.g. Rave, Medrio, Veeva) and tools like RTSM, ePRO, and tSDV - Strong expertise in project financials, reporting, and cross-functional collaboration - Comfortable representing CDM in external audits and contributing to continuous improvement initiatives Benefits - Salary based on experience - 20 days annual leave - Monthly allowance for employees working from home - Flexible working hours to support a healthy work/life balance - Medical insurance paid for each employee - 7.5% contribution towards an employee’s retirement annuity plan - Recognition gifts for long service (5th, 10th, 15th, or 20th anniversary)

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.