Ascensus is the leading independent technology and service platform powering savings plans across America, providing products and expertise that help nearly 16 million people save for a better today and tomorrow.
Section 1: Position Summary
A Senior Data Analytics Translator at Ascensus is expected to align our data science capabilities with our business objectives, acting as a critical bridge between technical data associates and the stakeholders deriving the usefulness of analytics results and interpretation thereof. This role ensures that complex insights are understood and converted into action initially focused on marketing growth strategies. The Senior Data Analytics Translator will have experience in financial services with retirement industry domain knowledge preferred. They should have proven success working interdepartmentally to recommend and influence the next best actions that accelerate growth. This role will identify high-impact business challenges, work with data engineers, scientists and analysts to collaborate with stakeholders on analytical solutions that deliver outcomes.
Section 2: Job Functions, Essential Duties and Responsibilities
Key Responsibilities
- Use Case Ownership & Lead: Own portfolio of related use cases in partnership with senior leaders. Initial responsibilities to accelerate Retirement marketing analytics and growth. Partner with stakeholders to identify, prioritize, and define high-value problems that can be solved using AI and advanced analytics. This position is expected to identify thematic issues and opportunities across projects, bringing insights from other projects to benefit current project goals.
- Analytics Alignment: Convert business goals into technical requirements for data scientists and engineers, ensuring the analytics deliverables drive solutions to the core business problem. Guide the technical work to optimize impact on business problems.
- Insight Synthesis: Synthesize complex model results into clear, actionable recommendations for non-technical stakeholders through compelling data storytelling. Effectively right size communication content to varying stakeholders from all levels of leadership. Optimize use of AI and other analytics tools to improve reporting and communications that best inform. Use BI tools to turn raw technical outputs into executive-level narratives. Maintain familiarity with external research and benchmarks, qualitative research and analytics deliverables beyond the specific project to consider and coalesce relevant insights into the data story and recommendations.
- Outcome Focus: Ensure defined success metrics align with business goals. Drive optimal business decisions by providing quantitative and qualitative data analysis, forecasts, propensity observations, predictions, insights and trends to decision makers. Be a proponent of personalization and other tactics to optimize outcomes incorporating new technologies and methods in actions.
- Project Governance: Manage the analytics life cycle for assigned projects and programs from ideation to production, including tracking KPIs to validate the business impact of data solutions. Own timeline and deliverables of the projects undertaken with focus on stakeholder satisfaction, success metrics and on time delivery. Ensure technical associates stay aligned with business goals in their efforts. Assist with project definition and planning. Rely on a multi-layered tech stack that balances deep data exploration with high-level business communication and effective project oversight.
- Adoption & Change Management: Drive organizational adoption of analytical tools. Foster a data-driven culture by educating users on how to interpret and execute on insights.
- Ascensus Information Security
- Responsible for protecting, securing, and proper handling of all confidential data held by Ascensus to ensure against unauthorized access, improper transmission, and/or unapproved disclosure of information that could result in harm to Ascensus or our clients.
- Our I-Client service philosophy and our Core Values of People Matter, Quality First and Integrity Always® should be visible in your actions on a day-to-day basis showing your support of our organizational culture.
Supervision
Section 3: Experience, Skills, Knowledge Requirements
Required skills:
- Domain Expertise: Deep knowledge of retirement industry and critical metrics (e.g., distribution, sales, revenue, customer retention) and how they impact the company’s profit and loss. If not retirement, an adjacent financial industry with proven success incorporating data insights in growth initiatives.
- Technical Fluency: A strong understanding of quantitative analytics, including the ability to identify which business problems fit specific models, multi-variate testing and/or inclusion of qualitative analysis to help lead solutioning and execution to results. Excellent analytical skills
- Project Management: Proficiency in data science analytics cycle management and agile frameworks that benefit a full feedback loop. and tools to manage the data science life cycle.
- Relationship building and influence: Ability to handle more complex organizational politics and cross-functional conflicts. Exceptional stakeholder management to build trust, influence solutions and ensure continued progress to achieve goals.
- Communication: Excellent oral and written communication skills providing examples of how data visualization and storytelling were used to inform resulting in actionable decisions and valuable outcomes. Ability to ask key appropriate questions to gain clarity of business problems and hypotheses to optimize recommendations and use of data analytics.
- Education: A bachelor's or master's degree in a STEM field (Statistics, Mathematics, Computer Science) or Business with a heavy focus on data literacy.
- 5+ years of relevant experience in an analytics translator role or related experience.
- Experience must include projects that span multiple departments frequently presenting to VP and executive level leadership.
- Tools and technology experience necessary for role
- Business Intelligence and visualization tools ideally with Microsoft solutions; or transferrable experience with other tools
- AI-Powered decision support and efficiency; Experience using tools like Co-pilot, Cursor or others to improve efficiency, automate visualizations, analysis and analytics documentation
- Using analytics tools that are low code or no code such as SQL and Knime
Preferred knowledge, skills, and abilities:
- Experience with Microsoft SSIS
- Experience with relational databases: Sybase ASE, Oracle, SQL Server or other.
- Experience with analytic platforms (data mining, predictive modeling, e.g. Knime) and Python
We are proud to be an Equal Opportunity Employee
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