Role Description Own the full data science engine for a priority vertical, from business problem to deployed model to live ROAS performance, driving measurable revenue and media efficiency. This is a hands-on, in-the-weeds role: you are heavily immersed in the data and the modeling, framing the business problem directly with stakeholders, building and validating the model, handing the ML-engineering last mile to your ML engineering partner, and staying engaged through deployment, monitoring, and performance analysis. You will start focusing on Insurance and Advertiser Quality, with scope that broadens over time. Your primary metric is ROAS. Outcomes - Own the Insurance vertical's primary modeling work end-to-end with measurable ROAS impact - Deliver buying models that maintain positive ROAS and quality - Drive lead quality improvements across our portfolio of brands: Messaging, Funnels, Content/Listicles, and more resulting in measurable impact to revenue growth - Establish trusted, direct partnership with vertical business stakeholders - Produce trusted output: validated, documented, low correction burden - Identify and leverage net-new modeling opportunities the business has not flagged Qualifications - Proven experience in digital marketing, performance marketing, or the leadgen industry - Building adtech algorithms and supporting user acquisition or paid media modeling (highly desired) - Strong modeling fundamentals: the ability to build effective models that drive business impact - Multi-year, hands-on experience building and deploying ML solutions in the AWS cloud - Hands-on experience across core technique areas: multi-armed bandit / reinforcement learning, recommendation and ranking systems (content-based, collaborative filtering, hybrid), funnel and monetization optimization, LTV modeling - Expert Python and SQL - 5+ years in a hands-on, in-the-weeds applied data science role delivering measurable business impact Requirements - Sophisticated ML at companies where paid digital media is core to the business model (nice to have) - Creative embeddings work: incorporating embeddings of creatives, videos, headlines, and search into paid media models (nice to have) - Insurance domain experience (nice to have) - Creating state-of-the-art Ad Ranking algorithms (nice to have) - Modeling against ad-platform data points (Google, Meta, native) (nice to have) - LLMs / deep learning applied to personalization or content (nice to have) - Familiarity with Looker (nice to have) Benefits - Base salary: $175,000 to $200,000 per year, paid semi-monthly - Compensation package includes a base salary, profit-sharing bonus, and competitive benefits - Performance-driven company: future increases based on company and personal performance

Role Description Own the full data science engine for a priority vertical, from business problem to deployed model to live ROAS performance, driving measurable revenue and media efficiency. This is a hands-on, in-the-weeds role: you are heavily immersed in the data and the modeling, framing the business problem directly with stakeholders, building and validating the model, handing the ML-engineering last mile to your ML engineering partner, and staying engaged through deployment, monitoring, and performance analysis. You will start focusing on Insurance and Advertiser Quality, with scope that broadens over time. Your primary metric is ROAS. Outcomes - Own the Insurance vertical's primary modeling work end-to-end with measurable ROAS impact - Deliver buying models that maintain positive ROAS and quality - Drive lead quality improvements across our portfolio of brands: Messaging, Funnels, Content/Listicles, and more resulting in measurable impact to revenue growth - Establish trusted, direct partnership with vertical business stakeholders - Produce trusted output: validated, documented, low correction burden - Identify and leverage net-new modeling opportunities the business has not flagged Qualifications - Proven experience in digital marketing, performance marketing, or the leadgen industry - Building adtech algorithms and supporting user acquisition or paid media modeling (highly desired) - Strong modeling fundamentals: the ability to build effective models that drive business impact - Multi-year, hands-on experience building and deploying ML solutions in the AWS cloud - Hands-on experience across core technique areas: multi-armed bandit / reinforcement learning, recommendation and ranking systems (content-based, collaborative filtering, hybrid), funnel and monetization optimization, LTV modeling - Expert Python and SQL Requirements - 5+ years in a hands-on, in-the-weeds applied data science role delivering measurable business impact. Nice to Haves - Sophisticated ML at companies where paid digital media is core to the business model - Creative embeddings work: incorporating embeddings of creatives, videos, headlines, and search into paid media models - Insurance domain experience - Creating state-of-the-art Ad Ranking algorithms - Modeling against ad-platform data points (Google, Meta, native) - LLMs / deep learning applied to personalization or content - Familiarity with Looker Benefits - Base salary: $175,000 to $200,000 per year, paid semi-monthly - Compensation package includes a base salary, profit-sharing bonus, and competitive benefits - Performance-driven company: future increases based on company and personal performance

Title: Senior Data Scientist, Responsible AI Location: Remote United States Type: Regular Job Description: Our vision for the future is based on the idea that transforming financial lives starts by giving our people the freedom to transform their own. We have a flexible work environment, and fluid career paths. We not only encourage but celebrate internal mobility. We also recognize the importance of purpose, well-being, and work-life balance. Within Empower and our communities, we work hard to create a welcoming and inclusive environment, and our associates dedicate thousands of hours to volunteering for causes that matter most to them. Chart your own path and grow your career while helping more customers achieve financial freedom. Empower Yourself. ***Applicants must be authorized to work for any employer in the U.S. We are unable to sponsor or take over sponsorship of an employment visa at this time, including CPT/OPT.*** The Senior Data Scientist of Responsible AI serves as a senior individual contributor within Empower’s Responsible AI (RAI) team. This role embeds directly with multiple AI delivery teams as a matrixed partner, ensuring AI and GenAI systems are measurable, transparent, safe, and aligned with Responsible AI principles. The position focuses on evaluation methodology, model behavior analysis, and operationalizing Responsible AI practices in collaboration with engineering, QA, security, and governance partners. What you will do: - Lead evaluation and validation of AI and GenAI systems, including assessment of hallucination, fairness, robustness, explainability, and other model behavior risks. - Design and implement repeatable evaluation workflows, benchmark datasets, and structured model behavior tests. - Serve as the Responsible AI data science partner for assigned AI delivery teams, guiding the integration of RAI metrics, guardrails, and evaluation practices. - Translate research findings and experimental methods into scalable, platform-ready evaluation capabilities. - Collaborate with AI/ML engineers and QA analysts to align evaluation logic with testing pipelines and deployment workflows. - Support the creation of model cards, evaluation documentation, and transparency artifacts required for governance and review. - Provide Responsible AI consultation to product, engineering, risk, legal, and governance stakeholders. - Mentor junior and mid-level data scientists on evaluation design, experimental rigor, and Responsible AI practices. What you will bring: - Bachelor’s degree in Computer Science, Statistics, Mathematics, or a related field, or equivalent experience. - 6+ years of professional data science experience. - Demonstrated experience developing or evaluating AI/ML systems in production or pre-production environments. - Strong grounding in experimental design, statistical analysis, and model evaluation methodology. - Experience collaborating with engineering and product teams in an agile, iterative delivery environment. - Proficiency in Python and SQL for data analysis and evaluation workflows. Experience working with modern cloud platforms such as AWS. - Strong communication skills and ability to operate effectively in a matrixed team model. Technology Environment - Cloud platforms such as AWS, including managed data and ML services. - Data storage and retrieval technologies such as relational and NoSQL databases. - Data analysis and visualization tools such as Python libraries, QuickSight, Tableau, or Power BI. - Collaboration and delivery tools supporting agile development and cross-functional workflows. Security and Risk Awareness - Contribute to Responsible AI and security-by-design practices by ensuring evaluation methods consider safety, misuse, and model risk. - Partner with engineering, security, and governance teams to identify, document, and mitigate AI-related risks surfaced through evaluation activities. - Support evolving security and risk requirements as they relate to AI system behavior, testing, and governance reviews. What Will Set You Apart - Experience evaluating Generative AI or LLM-based systems. - Hands-on work with explainability, fairness analysis, hallucination detection, or robustness testing techniques. - Familiarity with Responsible AI principles, governance frameworks, or model documentation practices. - Experience translating research or experimental methods into repeatable, production-aligned workflows. This job description is not intended to be an exhaustive list of all duties, responsibilities and qualifications of the job. The employer has the right to revise this job description at any time. You will be evaluated in part based on your performance of the responsibilities and/or tasks listed in this job description. You may be required perform other duties that are not included on this job description. The job description is not a contract for employment, and either you or the employer may terminate employment at any time, for any reason. #PJT What we offer you We offer an array of diverse and inclusive benefits regardless of where you are in your career. We believe that providing our employees with the means to lead healthy balanced lives results in the best possible work performance. - Medical, dental, vision and life insurance - Retirement savings – 401(k) plan with generous company matching contributions (up to 6%), financial advisory services, potential company discretionary contribution, and a broad investment lineup - Tuition reimbursement up to $5,250/year - Business-casual environment that includes the option to wear jeans - Generous paid time off upon hire – including a paid time off program plus ten paid company holidays and three floating holidays each calendar year - Paid volunteer time — 16 hours per calendar year - Leave of absence programs – including paid parental leave, paid short- and long-term disability, and Family and Medical Leave (FMLA) - Business Resource Groups (BRGs) – BRGs facilitate inclusion and collaboration across our business internally and throughout the communities where we live, work and play. BRGs are open to all. Base Salary Range $105,700.00 - $149,275.00 The salary range above shows the typical minimum to maximum base salary range for this position in the location listed. Non-sales positions have the opportunity to participate in a bonus program. Sales positions are eligible for sales incentives, and in some instances a bonus plan, whereby total compensation may far exceed base salary depending on individual performance. Actual compensation offered may vary from posted hiring range based upon geographic location, work experience, education, licensure requirements and/or skill level and will be finalized at the time of offer. Equal opportunity employer • Drug-free workplace We are an equal opportunity employer with a commitment to diversity. All individuals, regardless of personal characteristics, are encouraged to apply. All qualified applicants will receive consideration for employment without regard to age (40 and over), race, color, national origin, ancestry, sex, sexual orientation, gender, gender identity, gender expression, marital status, pregnancy, religion, physical or mental disability, military or veteran status, genetic information, or any other status protected by applicable state or local law. ***For remote and hybrid positions you will be required to provide reliable high-speed internet with a wired connection as well as a place in your home to work with limited disruption. You must have reliable connectivity from an internet service provider that is fiber, cable or DSL internet. Other necessary computer equipment, will be provided. You may be required to work in the office if you do not have an adequate home work environment and the required internet connection.***

• Establish and lead the company's first centralized analytics function. • Define the long-term analytics vision, roadmap, and operating model. • Establish data governance standards, metric definitions, and reporting frameworks. • Partner with executive leadership to enable data-driven strategic decisions. • Direct and mentor embedded analysts across multiple business functions. • Design and implement the end-to-end analytics technology stack. • Select and deploy data warehousing, transformation, visualization, and reporting solutions. • Build scalable analytics infrastructure to support multiple financial products. • Develop a canonical data model across the organization. • Ensure data quality, consistency, accessibility, and governance. • Design and implement multi-touch attribution across various marketing channels. • Build unified customer journey tracking. • Create real-time executive dashboards and KPI reporting. • Establish a company-wide hypothesis testing and experimentation framework. • Collaborate closely with Marketing, Product, Technology, Operations, and Commercial teams. • Lead, coach, and develop embedded analysts.