Analytics Functionality Analyst

Earnix is the premier provider of mission-critical, cloud-based intelligent decisioning across pricing, rating, underwriting, and product personalization. These fully-integrated solutions provide ultra-fast ROI and are designed to transform how global insurers and banks are run by unlocking value across all facets of the business. Earnix has been innovating for insurers and banks since 2001 with customers in over 35 countries across six continents and offices in the Americas, Europe, Asia Pacific, and Israel.

We are seeking an Analytics Functionality Analyst to join our Analytics engineering group. In this role, you will serve as a crucial partner to the Product Manager, facilitating the translation of complex analytics into actionable steps for functional software delivery. This hybrid position combines robust analytical skills with a keen understanding of engineering processes, allowing the Product Manager to focus on the strategic “what” and “why,” while you ensure clarity on the operational “how.”

What you’ll do:

• Feature Translation: Convert high-level analytical concepts and product features into clear, functionally defined user stories that capture algorithmic and statistical nuances for the engineering team.
• Collaboration with Engineering Teams: Work closely with developers and data scientists to assess feature feasibility, identify edge cases, and establish thorough testing and validation criteria within the engineering environment.
• Customer Engagement: Participate in technical discussions with customers, especially when deep modeling insights or analytics expertise are required, to gather feedback that informs engineering decisions.
• Documentation Authority: Own the documentation of analytics functionality, positioning yourself as the internal authority on modeling logic and assumptions, thereby ensuring consistency and clarity across engineering projects.
• Support Engineering Testing: Drive the testing and validation of implemented models and features, ensuring they function as expected from an analytics perspective and contributing to overall product quality.

You’ll do it using:

• At least 2 years of hands-on experience working within or alongside data science and engineering teams, providing valuable insights into engineering processes.
• Strong background in statistics, machine learning, or actuarial science, enabling effective navigation of complex analytical concepts within an engineering context.
• Proven ability to write precise and unambiguous functional requirements that effectively guide engineering development.
• Comfort interfacing with both technical engineering teams and customer stakeholders, fostering effective communication across diverse groups.
• A pragmatic, delivery-oriented mindset focused on achieving project goals efficiently while maintaining quality.
• A proactive problem-solver with the ability to adapt to evolving priorities and initiatives in a dynamic engineering environment