Senior Strategy and Analytics Lead

MyPlanAdvocate

17h

About The Position

The Senior Strategy and Analytics Lead will be responsible for performing a variety of analytical duties to drive business growth and efficiency. This role involves deep dives into funnel analysis across marketing, sales, operations, product, and compliance systems. The lead will translate ambiguous business goals into structured problem statements and test plans, identify opportunities for margin expansion, conversion optimization, and cost efficiency, and design scalable experimentation and measurement frameworks. Additionally, the role will leverage AI tools to accelerate modeling and automation, and build analytical assets to present executive-ready recommendations. This position requires a Bachelor's Degree in Data Science, Computer Science, Information Systems, or Management Information Systems.

Requirements

Bachelor's Degree in Data Science, Computer Science, Information Systems, or Management Information Systems.
Experience in funnel analysis across marketing, sales, operations, product, and compliance systems.
Experience analyzing conversion across acquisition funnels.
Experience investigating drop-off points and identifying high-converting sources.
Experience analyzing call-center metrics and connecting them to conversion.
Experience examining post-enrollment retention and identifying churn drivers.
Experience cross-referencing compliance and quality data with conversion outcomes.
Experience building cohort views by various segmentation criteria.
Experience translating ambiguous business goals into structured problem statements and test plans.
Experience leading scoping sessions with stakeholders.
Experience drafting structured test plans with specific components.
Experience documenting analytical assumptions, constraints, and limitations.
Experience building margin and unit-economics models.
Experience quantifying the impact of conversion-rate improvements.
Experience identifying high-cost-low-conversion segments and recommending reallocation.
Experience analyzing agent productivity and recommending improvements.
Experience partnering with finance to reconcile analytical outputs.
Experience recommending process automation opportunities.
Experience building experimentation frameworks for acquisition and enrollment funnels.
Experience owning source-of-truth metric definitions.
Experience designing A/B test infrastructure.
Experience establishing experimentation guardrails.
Experience maintaining a library of measurement assets.
Experience integrating AI tool outputs with business data.
Experience using AI-assisted modeling and scenario tools for root-cause analysis.
Experience applying AI-driven lead scoring and intelligent routing logic.
Experience identifying and automating operational analytics tasks with AI.
Experience evaluating, prototyping, and rolling out AI tools for analytical workflows.
Experience building and maintaining executive dashboards.
Experience producing deep-dive analyses for senior leadership.
Experience translating analytical findings into executive summaries with recommendations.
Experience presenting quantitative analysis to leadership.

Responsibilities

Perform funnel analysis across Marketing, Sales, Operations, Product, and Compliance Systems, analyzing conversion from lead capture through enrollment submission.
Investigate drop-off points across acquisition channels to identify sources with the highest end-to-end enrollment conversion.
Partner with the licensed-agent operations team to analyze call-center metrics and connect them to conversion.
Examine post-enrollment retention by plan type and carrier to identify churn drivers.
Cross-reference compliance and quality data with conversion outcomes to identify where compliance friction reduces throughput.
Build cohort views by lead source, agent, region, plan type, and enrollment period to detect seasonal and structural patterns.
Translate ambiguous business goals into structured problem statements and test plans by working with the COO and senior leadership.
Lead scoping sessions with stakeholders to align on success criteria, target metrics, scope boundaries, and implementation owners.
Draft structured test plans specifying target metrics, control conditions, expected effect size, sample size, statistical significance threshold, and decision rules.
Document analytical assumptions, constraints, and limitations for leadership decision-making.
Build margin and unit-economics models segmented by various business dimensions.
Quantify the impact of conversion-rate improvements to prioritize analytics investment.
Identify high-cost-low-conversion lead segments and recommend reallocation of marketing spend or routing changes.
Analyze agent productivity to recommend training, scheduling, or workflow changes.
Partner with finance to reconcile analytical outputs against the commission model and carrier payment cycles.
Recommend process automation opportunities where data shows manual work creates cost leakage.
Build the experimentation backbone for consumer-facing acquisition and enrollment funnels.
Own source-of-truth metric definitions across teams to ensure consistent measurement.
Design A/B test infrastructure for various elements of the acquisition and enrollment process.
Establish guardrails for experimentation to allow non-analytics teams to run tests responsibly.
Maintain a reusable library of measurement assets for future analyses.
Integrate outputs from AI tools with conversion, retention, and revenue data to identify predictive behavioral patterns.
Use AI-assisted modeling and scenario tools to accelerate root-cause analysis.
Partner with teams to apply AI-driven lead scoring and intelligent routing logic.
Identify operational analytics tasks that can be automated with AI tooling and build the underlying logic.
Evaluate, prototype, and roll out emerging AI tools for analytical workflows.
Build and maintain executive dashboards covering key KPIs.
Produce deep-dive analyses for senior leadership on strategic questions.
Translate analytical findings into executive summaries with clear recommendations and projected financial impact.
Present at leadership meetings and serve as the quantitative voice in strategic planning and investor-facing analysis.
Maintain the analytical asset library used by leadership to inform day-to-day decisions.