Job Description

Job Description

About LeaseLock \n

LeaseLock replaces traditional security deposits with lease insurance and other financial tools that reduce risk, recapture revenue, and help property owners and operators run more efficient, profitable portfolios.

This role sits at the center of LeaseLock's risk and analytics function, bridging our Analytics, Actuarial, and Data Science teams with the executives, finance, and go-to-market stakeholders who rely on their output.

This is not a technical data analyst role—we already have established data analysts and data engineers producing the core data models and infrastructure. What we need is a strategic problem solver who can take ambiguous, high-stakes questions from the CEO, CFO, or sales leadership and deliver clear, data-backed answers framed through a practical business lens, partnering seamlessly with technical teams along the way.

A typical week might include:

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• Writing SQL queries and using Excel to resolve high-priority, fast-paced ad hoc requests from Leadership, Finance, Sales, Product, and Client Services.
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• Defining standardized business logic for emerging metrics and transitioning recurring ad hoc requests into automated reporting workflows.
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• Auditing and sanity-checking analytical deliverables to ensure calculations are logical and mathematically sound Tracking and evaluating client performance and pre-emptively providing proactive recommendations to business stakeholders.
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• Bridge Risk & Analytics team (Analytics, Actuarial, Data Science) and business stakeholders across Leaders Finance, Sales, Client Services.
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• Field high-stakes, time-sensitive questions from leadership; frame them into structured analytical plans and partner with technical teams to deliver clear, data-backed answers.
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• Perform quick-turn exploratory data analysis and partner with technical and product teams to establish clear data definitions for emerging business metrics.
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• Identify recurring ad hoc requests and transform them into standardized, scalable, and automated workflows.
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• Track, monitor, and analyze portfolio performance, partnering with Client Services to prepare data-driven deliverables and reviews.
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• Partner on loss-ratio forecasting, underwriting, and performance reporting to turn data analytics, data science, and actuarial outputs into actionable recommendations for leadership, finance, and external partners..
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• Act as the ultimate quality control layer for data outputs—auditing, validating, and reconciling outputs to ensure they are logically sound and coherent .
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Our ideal candidate will have experience as listed below, or similar experience to draw on for the responsibilities above.

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• Experience: 5+ years in a Business Analyst, Data Analyst, or Technical Product Analyst role, ideally at an Insurtech  company.
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• Technical fluency: Hands-on proficiency with SQL and Excel; ability to sanity-check an analysis and speak the language of Data Science, Data Analytics, and Engineering, without being the primary data analyst.
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• Self-starter & high ownership: Comfortable operating with real ambiguity and limited oversight, and able to partially define the role as it grows.
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• Problem-solving: Highly adaptable and able to solve ambiguous, fast-evolving business questions.
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• Great communicator: Clear and regular communication with internal and external partners; able to bridge the gap between engineering and business conversations, and unafraid to voice concerns.
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• Collaboration: A proven track record of building relationships, earning trust, and aligning stakeholders across functions.
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• Executive presence: A proven track record of communicating confidently and credibly with C-suite executive, and senior stakeholders, including fielding ambiguous questions on the spot
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• Priority management: A track record of managing competing priorities across multiple functions (Finance, Sales, Client Services, Product, Engineering) with composure.
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• Domain knowledge: Insurance  domain knowledge; comfortable with the language of underwriting, premiums, coverage, and loss ratios without needing to be taught the basics.
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