Role Description As a Data Scientist III at Indeed, you will leverage your expertise in data science, statistics, AI, and machine learning to take on complex product, marketing, and business challenges. You will design and implement analytical solutions that guide decisions, optimize product performance or marketing campaigns, and create measurable impact across the organization. - Oversee the design and execution of advanced analyses, experiments, and machine learning models to address complex questions. - Translate data into actionable insights to guide product, marketing, and business decisions. - Develop and maintain scalable, robust data pipelines and models for large-scale product data. - Collaborate with engineering and product teams to integrate data science solutions into product workflows. - Mentor and support other data scientists, promoting knowledge sharing and best practices. - Contribute to the development of AI agents and skills, methodologies, and processes that improve the efficiency and impact of the data science team. - Communicate findings clearly through presentations, visualizations, and documentation for diverse audiences. Qualifications - Requires a Bachelor’s degree in Computer Science, Mathematics, or Statistics, and a minimum of 8 years of related experience; or a Master’s degree with a minimum of 6 years of experience; or a PhD with 3 years experience. - Expertise in A/B testing and experimentation is required. - Solid foundation in data science methods and technologies. - Able to influence technical direction and contribute to long-term planning. - Able to work effectively with other teams and mentor colleagues. - Focused on delivering high-quality, impactful solutions that contribute to business goals. - Excellent written and verbal communication in English, effective with technical and business audiences. Salary Range Disclaimer The salary range for this role reflects the minimum and maximum compensation for the role. Offers are typically made between the range minimum and the range midpoint. Actual compensation will be determined based on job-related skills, experience, and expertise, as evaluated during the interview process. The range(s) listed is just one component of Indeed's total compensation package for employees. Other rewards may include quarterly bonuses, Restricted Stock Units (RSUs), a Paid Time Off policy, and many region-specific benefits. Compensation may also vary based on where a role is performed, as work locations are grouped into geographic pay tiers to reflect cost of labor differences in different geographic markets. - Tier 1 - United States of America: 150,000 - 224,000 USD per year - Tier 2 - United States of America: 166,000 - 250,000 USD per year - Tier 3 - United States of America: 182,000 - 274,000 USD per year - Tier 5 - United States of America: 207,000 - 311,000 USD per year EEO and Accommodations Indeed is deeply committed to building a workplace and global community where inclusion is not only valued, but prioritized. We’re proud to be an equal opportunity employer, seeking to create a welcoming and diverse environment. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, family status, marital status, sexual orientation, national origin, genetics, neuro-diversity, disability, age, or veteran status, or any other non-merit based or legally protected grounds. Indeed provides reasonable accommodations to qualified individuals with disabilities in the employment application process. To request an accommodation, please visit this link . If you are requesting accommodation for an interview, please reach out at least one week in advance of your interview. Inclusion & Belonging Inclusion and belonging are fundamental to our hiring practices and company culture, forming an integral part of our vision for a better world of work. At Indeed, we’re committed to the wellbeing of our employees and on a mission to make this the best place to work and thrive. - We value diverse experiences, including those who have had prior contact with the criminal legal system. - We are committed to providing individuals with criminal records, including formerly incarcerated individuals, a fair chance at employment. - Those with military experience are encouraged to apply. - Equivalent expertise demonstrated through a combination of work experience, training, military experience, or education is welcome. Reference ID 47084 The deadline to apply to this position is 6/12/2026. Job postings may be extended at the hiring team’s discretion based on applicant volume.

Role Description We are currently seeking a Principal Data Scientist for Enverus Power and Renewables, who will create measurable customer value. You will partner closely with Product Management and Engineering to define and execute short- and long-term data roadmaps, applying advanced statistical, machine learning, and data engineering techniques across multiple product areas. - Strategic Data Analysis: Lead strategic data analysis initiatives, leveraging advanced statistical techniques, predictive modeling, and machine learning algorithms to uncover valuable insights. Analyze complex data sets to identify patterns, trends, and correlations that inform product strategy, optimization, and innovation. - Product Strategy Alignment: Collaborate closely with product managers, executives, and stakeholders to align data analysis efforts with the overall product strategy. Provide strategic guidance and insights to drive product roadmap prioritization, feature development, and market positioning. - Business Impact Assessment: Assess the impact of product initiatives on key performance metrics, customer satisfaction, and business outcomes. Conduct rigorous analysis to measure the effectiveness of product changes, identify causal relationships, and provide recommendations for continuous improvement. - Data Governance and Infrastructure: Oversee data governance processes, ensuring data integrity, security, and compliance. Collaborate with data engineering and IT teams to optimize data collection, storage, and retrieval processes. Drive improvements in data infrastructure and data management practices. - Thought Leadership and Innovation: Stay at the forefront of data analysis methodologies, tools, and industry trends. Champion innovative approaches to data analysis, experiment design, and modeling techniques. Act as a thought leader in the field of data analytics, influencing the organization's data-driven culture. - Stakeholder Collaboration: Collaborate closely with cross-functional teams, including product managers, engineers, data scientists, and executives, to provide insights and recommendations. Influence decision-making processes by effectively communicating complex data insights and demonstrating the value of data-driven strategies. - Team Leadership and Mentorship: Provide leadership and mentorship to the data analytics team. Foster a culture of continuous learning, collaboration, and growth. Guide and mentor junior analysts, helping them develop their analytical skills and business acumen. Qualifications - Expertise in advanced data analysis techniques, including statistical modeling, predictive analytics, and machine learning. - Proficiency in programming languages such as Python, and strong SQL skills for data extraction and manipulation. - Strong leadership and influencing skills to effectively collaborate with cross-functional teams, influence decision-making processes, and drive organizational change. - Ability to inspire and mentor a team of data analysts. - Extensive experience in data manipulation, data querying, and database management. - Familiarity with data warehousing concepts and data integration processes. - Strong critical thinking and problem-solving abilities to tackle complex business challenges. - Demonstrated ability to think strategically and envision the future of data analytics in the organization. - Excellent collaboration and relationship-building skills to establish strong partnerships with product managers, executives, and stakeholders. - In-depth knowledge of data governance best practices, data security, and regulatory compliance. Requirements - Bachelor's degree from a three or four-year college or university. - 4-6 years of relevant work experience. Benefits - Medical - Dental - Vision - Income Protection (disability, life/AD&D, critical illness, accident) - Employee Assistance Program (EAP) - Healthcare Spending Account (HSA), Commuter - Lifestyle & Wellbeing Program - Pet Insurance

Role Description Rain is the world's first AI Financial Health Platform, serving 3.5 million employees at leading organizations like McDonald's, Marriott, and T-Mobile. Rain works in the background to optimize every employee's financial life to prevent shortfalls and build long-term stability. About the Team: Our data science team sits at the center of Rain's product. We're a small, senior team embedded in a fast-moving fintech, which means the models we build go directly into production decisions — credit risk scoring, balance forecasting, personalized financial insights — and the impact is immediate and measurable. We work closely with product, engineering, and compliance, and we operate like owners: defining problems, building solutions, and monitoring them in production. If you're the kind of data scientist who gets energized by seeing your work move the needle on a real product — not just a dashboard — this team was built for you. This role is based remotely in EMEA. You'll be a key early hire on our international data science presence, working across time zones with our U.S.-based team and contributing to how we scale our ML function globally. What You’ll Do - Run end-to-end experiments: feature engineering, model selection, A/B testing, and production monitoring - Build and maintain scalable, well-documented pipelines that keep models healthy in production - Design, train, and deploy ML and Agentic models that drive core product decisions, including credit risk, forecasting, and personalized recommendations - Collaborate with product and engineering to translate business problems into well-scoped modeling tasks - Communicate model behavior and findings to both technical and non-technical stakeholders Who You Are - You thrive in ambiguity — you can take a loosely defined business problem, ask the right questions, and turn it into a well-scoped modeling task without waiting for a perfect brief - You are a strong cross-functional collaborator who builds trust with product, engineering, and compliance partners and can speak their language - You have a bias toward shipping — you know when a model is good enough to get into production and how to iterate from there, rather than optimizing in isolation - You take ownership end-to-end: from a messy raw dataset to a monitored production model, you don't hand things off and walk away - You communicate with clarity — you can walk a skeptical stakeholder through a model's tradeoffs without leaning on jargon - You care deeply about model behavior in the real world, not just on a held-out test set - You mentor and elevate the people around you, and you're energized by working somewhere where the stakes are real Qualifications - Python and core ML libraries (pandas, scikit-learn, PyTorch, or TensorFlow) - SQL and working with large, complex datasets - Experience with LLMs and NLP techniques (fine-tuning, RAG, prompt engineering or similar) - Communication skills to explain models trade offs - Solid understanding of statistical modeling, experimentation, and model evaluation - Experience taking models from prototype to production - Familiarity with agentic frameworks (e.g. Langchain) and agent orchestration and evaluation Diversity, Equity and Inclusion Commitments As part of our dedication to the diversity of our workforce, Rain is committed to Equal Employment Opportunity and does not discriminate based on race, religion, color, national origin, ethnicity, gender, sex (including pregnancy), protected veteran status, age, disability, sexual orientation, gender identity, gender expression, or any unlawful criterion existing under applicable federal, state, or local laws. If you need assistance or accommodation due to a disability, you may contact us at HR-US@rain.us. What’s Next Ensuring a smooth and enjoyable candidate experience is critical for us. Our interview process tends to take about 4 weeks to complete, but may fluctuate depending on the role. Learn more about our hiring process here. Don’t be afraid to let us know if you need more flexibility.

Role Description What you’ll do: - Combine deep understanding of machine learning, advanced data analysis, statistical testing, and the ability to communicate insights effectively to both technical and non-technical stakeholders. - Operate as a full stack data scientist utilizing expertise in both machine learning and cloud technologies, while also growing and leading a team. - Lead data science projects through development lifecycle including offline evaluation, deployment, experimentation, feedback, and model improvements. - Formalize procedures about how models are expected to behave, creating definitions of outliers, developing methods to identify them systematically, and explaining why they are reasonable or identifying fixes. - Design, develop, and implement machine learning models for various applications, including but not limited to predictive analytics, natural language processing, generative AI, and computer vision for different retail applications. - Research and implement state-of-the-art machine learning algorithms to address specific business challenges. - Analyze large, complex data sets to extract actionable insights and identify trends, patterns, and opportunities. - Handle data collection, cleansing, and validation processes to ensure data integrity and reliability. - Collaborate with cross-functional teams, including data scientists, software engineers, and domain experts, to understand requirements and deliver effective solutions. - Document code, algorithms, and processes to facilitate knowledge sharing and ensure reproducibility. - Provide technical guidance in best practices for model development to the data science team. Qualifications - Master’s degree in Data Science, Math, Statistics, Computer Science, or related field and 4 years of experience as a Computer and Information Systems Manager or a related position/occupation. - Ph.D. degree in Data Science, Math, Statistics, Computer Science, or related field and 2 years of experience as a Computer and Information Systems Manager or a related position/occupation. Requirements - Apply advanced mathematics and data science methodologies. - Standard machine learning and statistical techniques including predictive models (time series, regression, etc.), classification, forecasting. - Programming in Python and ML frameworks. - Developing and deploying advanced machine learning models and algorithms in a production environment. Benefits - Base salary range: $189,684 to $296,000 per year. - Eligible for 401k and a new hire and annual equity grant. - C08+ positions may also be eligible for annual bonus. - Different types of insurance and benefits, such as medical/Rx, vision, dental, life, disability, hospital indemnity, critical illness, and accident. - Parental leave, family services benefits, backup dependent care, flexible spending accounts, telemedicine, pet adoption reimbursement, employee assistance program. - Discounts including 10% off pet insurance and 20% off at Chewy.com. - Unlimited PTO for exempt salary team members, subject to manager approval. - Six paid holidays per year. - Eligibility for paid sick and family leave in compliance with applicable state and local regulations.