Data Scientist Lead

Ace

Coppell (TX)

Hybrid

USD 140,000 - 190,000

Full time

14 days+

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Benefits offered by this job

Health coverage for medical, dental,视n
401(K) saving plans with company match
Pension
Tuition assistance
Floating holidays and PTO for programs
Paid parental leave
Wellness programs
Employee discounts

Job summary

Auto Club Enterprises is seeking a Lead Data Scientist to act as a strategic internal consultant, solving business problems with data and driving efficiency for its 17 million members.

You will partner with stakeholders to formulate analytical approaches, analyze data from enterprise platforms, and apply advanced methods including machine learning and causal inference to deliver actionable insights and scalable solutions.

Qualifications

  • Bachelor's degree in a quantitative field.
  • 3+ years of professional data science/analytic experience.
  • 1+ year leading projects or mentoring teammates.
  • Advanced SQL skills for large datasets.
  • Proficient in Python for data analysis and ML.
  • Experience with cloud platforms (AWS/GCP) and modern data ecosystems.
  • Experience applying experimental design, hypothesis testing, and causal inference.
  • Experience deploying ML models in production.
  • Experience creating dashboards with Tableau or Power BI.
  • Strong ability to explain analytics to non-technical colleagues.

Responsibilities

  • Solve business problems by using data and analytics.
  • Partner with business teams to define challenges and deliver insights to improve efficiency and performance.
  • Pull, curate, and analyze data from enterprise data platforms and cloud environments.
  • Develop, validate, deploy, and monitor ML models in production.
  • Collaborate with data engineers to build scalable analytics solutions.
  • Operationalize models and automate workflows using AI and automation tools.
  • Communicate findings via dashboards and visualizations to stakeholders.

Skills

Statistics
Data analysis
Leadership
Communication

Education

Bachelor's degree in Statistics, Data Science, Computer Science, Mathematics, Engineering, Economics, or related field

Tools

Python
SQL
AWS
GCP
Databricks
Snowflake

Job description

Data Scientist Lead

As our Lead Data Scientist, you will act as an internal business consultant to help optimize every facet of this organization. You will solve problems and answer questions – using data – for other departments to help us reduce costs, reduce errors, and be a better organization for our 17 million members.

What You'll Do

Every day, you will help solve business problems presented by stakeholders using data. You will partner with business teams to understand challenges, formulate analytical approaches, and deliver actionable insights that improve operational efficiency, customer experience, and business performance.

You will pull, curate, and analyze data from enterprise data platforms and cloud environments using SQL, Python, or similar tools. You will apply statistical methods, hypothesis testing, causal inference, machine learning, and advanced analytics techniques to identify trends, determine root causes, evaluate business strategies, and measure outcomes.

You will work with large-scale datasets and collaborate closely with data engineers to build scalable analytical solutions. Depending on the business need, your work may include exploratory analysis, dashboard development, predictive modeling, experimentation, causal impact studies, or machine learning solutions deployed into production environments.

You will also design, develop, and maintain machine learning and predictive models that support business decision-making and operational efficiency. As part of your day-to-day responsibilities, you will identify opportunities to automate manual processes, streamline analytical workflows, and develop scalable solutions that improve accuracy, consistency, and speed across the organization. This may include leveraging machine learning, generative AI, intelligent agents, and workflow automation technologies to create data-driven solutions that enhance business processes and user experiences.

You will partner with data engineers and business stakeholders to operationalize models, AI-powered applications, and automated processes, ensuring they are scalable, maintainable, and deliver measurable business value. Using tools such as Tableau, Power BI, or other visualization platforms, you will communicate findings and recommendations to technical and non-technical stakeholders.

You will translate complex analytical concepts into clear business insights and influence decision-making across the organization.

As a senior contributor, you will lead projects, mentor junior data scientists, and help guide cross-functional initiatives from concept through implementation.

Note: This is a hybrid role; the candidate must reside within a 100-mile radius of our Costa Mesa, CA office and be available to work on-site 3 days a week on a regular basis, as well as 2–3 times per month for team meetings and collaboration days.

What You'll Need

To thrive in this role, you must have a strong foundation in statistics, data analysis, and business problem solving. You should be comfortable taking an ambiguous business problem, developing an analytical approach, and translating findings into actionable recommendations.

Required Qualifications
  • Bachelor's degree in Statistics, Data Science, Computer Science, Mathematics, Engineering, Economics, or a related quantitative field.

  • Minimum of 3 years of professional experience in data science, advanced analytics, business analytics, or a related field.

  • Minimum of 1 year of experience leading projects, mentoring team members, or managing cross-functional initiatives.

  • Advanced SQL skills with experience querying and analyzing large datasets.

  • Strong programming experience in Python for data analysis, statistical modeling, and machine learning.

  • Experience working with cloud platforms and modern data ecosystems, including AWS, Google Cloud Platform (GCP), Databricks, Snowflake, or similar technologies.

  • Experience applying statistical techniques such as experimental design, hypothesis testing, statistical inference, regression analysis, causal inference and impact measurement

  • Experience developing, validating, deploying, and monitoring machine learning models in production environments.

  • Experience creating dashboards and visualizations using Tableau, Power BI, or comparable tools.

  • Strong communication skills with the ability to explain technical concepts and analytical findings to non-technical audiences.

Preferred Qualifications
  • Experience in the insurance industry, including claims, underwriting, actuary, or operational analytics.

  • Experience supporting Agile teams and working in a sprint-based development environment.

  • Experience with automation, agentic workflows, and AI-driven business solutions.

Remarkable benefits:
  • Health coverage for medical, dental, vision
  • 401(K) saving plans with company match AND Pension
  • Tuition assistance
  • Floating holidays and PTO for community volunteer programs
  • Paid parental leave
  • Wellness programs
  • Employee discounts (membership, insurance,
  • travel, entertainment, services and more!)

Auto Club Enterprises is the largest club within the national AAA federation. We have nearly 17,000 employees in 24 states helping more than 18 million members. The strength of our organization is our employees. Bringing together and supporting different cultures, backgrounds, personalities, and strengths creates a team capable of delivering legendary, lifetime service to our members. When we embrace our diversity – we win. All of Us! With our national brand recognition, long-standing reputation since 1900, and constantly growing membership, we are seeking career-minded, service-driven professionals to join our team.

Through dedicated employees we proudly deliver legendary service and beneficial products that provide members peace of mind and value.

AAA is an Equal Opportunity Employer

Our organization participates in E-Verify

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