Analytics Engineer

Morgan & Morgan, P.A.•New York, NY

7h•$120,000 - $160,000•Onsite

About The Position

At Morgan & Morgan, the work we do matters. For millions of Americans, we’re their last line of defense against insurance companies, large corporations or defective goods. From attorneys in all 50 states, to client support staff, creative marketing to operations teams, every member of our firm has a key role to play in the winning fight for consumer rights. Our over 6,000 employees are all united by one mission: For the People.

Requirements

BS or MS in Engineering, Computer Science, Statistics, or related quantitative field.
4+ years of experience in data science, engineering, analytics, or forecasting in a corporate environment.
Demonstrated experience building and maintaining data models that influence operational or financial decisions.
Strong proficiency in SQL and Python (or R) for data transformation, statistical analysis, machine learning, and automation.
Familiarity with modern software engineering and cloud practices, including version control (Git), cloud platforms (Azure/AWS), agentic coding tools, containerization, CI/CD, and API development.
Experience developing dashboards and reports using modern BI tools (Power BI preferred).
Experience building and maintaining scalable ETL/ELT workflows, including data ingestion, transformation logic, validation checks, and production-ready analytical datasets.
Advanced quantitative modeling, analytical reasoning, and critical thinking skills.
Ability to communicate complex analytical concepts to both technical and non-technical audiences.
Demonstrated ability to manage ambiguity, prioritize effectively, and deliver results in a fast-paced environment.

Responsibilities

Design, build, and maintain forecasting and analytical models that support strategic planning, staffing, and financial decision-making.
Build and maintain internal tools, automations, and production-grade model deployments that scale the team’s analytical capabilities beyond ad hoc analysis.
Analyze complex operational and financial datasets to identify trends, risks, and opportunities.
Provide analytical support for executive leadership by responding to strategic inquiries, special initiatives, and emerging business needs.
Develop and monitor KPIs across business functions to ensure accurate performance measurement and alignment to goals.
Translate data into actionable insights through clear reporting, dashboards, and executive-ready presentations.
Improve and enhance analytical methodologies by incorporating new data sources, testing assumptions, and refining model parameters.
Partner cross-functionally with Operations, Finance, Marketing, and Legal teams to align forecasts and planning assumptions.
Conduct variance analysis and support root-cause investigations when results diverge from expectations.
Uses AI as a productivity and impact multiplier, embedding it into workflows to accelerate analysis, improve output quality, and scale.