We are looking for a highly skilled and motivated Sr. Data Scientist to join our Business Intelligence & Analytics team. In this role, you will serve as a key contributor in leveraging data, advanced analytics, and machine learning to solve high‑impact business challenges across Integrity.
The ideal candidate is highly analytical, curious, collaborative, and proactive—someone who seeks out challenges, develops innovative analytical solutions, and communicates insights in ways that influence decision-making. This role requires both technical excellence and strong business acumen, with the ability to translate complex data into actionable recommendations.
Key Responsibilities
Data Science & Advanced Analytics
- Develop, enhance, and operationalize machine learning models and advanced statistical solutions to support a wide range of business initiatives.
- Support segmentation, agent lifecycle analytics, and acquisition modeling as part of a broader portfolio of initiatives.
- Apply predictive methods to understand behavior, performance, and engagement across customer and agent populations.
- Utilize leading ML libraries and frameworks, including scikit-learn, TensorFlow, and others.
Business Insight & Strategy
- Partner with stakeholders across Operations, Marketing, Sales, Product, Distribution, and other business teams to deeply understand challenges and identify analytical opportunities.
- Translate complex analytical findings into clear, compelling, and actionable recommendations for both technical and non-technical audiences.
- Support strategic decision-making with predictive models, scenario analysis, and ROI assessments.
Data engineering & Technical Execution
- Extract, clean, transform, and structure large datasets using SQL, Python, and cloud-based tools.
- Develop scalable analytics pipelines and reusable analytical assets.
- Collaborate with data science and engineering partners to influence data architecture, improve data capture, and enhance data quality.
Cross-Functional Collaboration
- Serve as a subject matter expert in data science methodologies and best practices.
- Provide mentorship to analysts, data scientists, and cross-functional team members.
- Work closely with other analytics teams to align on methodologies, share knowledge, and ensure consistency across the organization.
- Contribute to the development of analytical standards, frameworks, and tools.
Domain Analytics (Beyond Segmentation & Acquisition)
- Support segmentation, agent lifecycle analytics, and acquisition modeling as part of a broader portfolio of initiatives.
- Apply predictive methods to understand behavior, performance, and engagement across customer and agent populations.
- Deliver insights that guide strategic growth, operational efficiency, and business planning.
Technical Skills
- Expertise in machine learning algorithms, including in‑memory processing (e.g., Pandas, PySpark, Dask) and ML frameworks such as scikit‑learn and TensorFlow.
- Strong Python or R skills for machine learning, statistical analysis, and automation.
- Proficiency in SQL for working with large-scale relational data.
- Experience with cloud platforms such as Snowflake, Azure, AWS, or GCP.
- Familiarity with modern data science workflows, feature engineering, MLOps concepts, and model lifecycle best practices.
- Experience building dashboards and interactive analytical tools (Power BI, Tableau, etc.).
Business & Soft Skills
- Ability to convert technical analytics outputs into business-friendly insights and recommendations.
- Strong communication and data storytelling skills, including experience presenting to leadership.
- Collaborative mindset and ability to work closely with non-technical stakeholders.
- Strategic thinker with strong problem‑solving and critical reasoning capabilities.
- Comfort operating in fast-paced, dynamic environments.
Experience
- 4-6 years of experience in data analytics preferably in insurance, financial services, agent‑driven businesses, or other data-rich industries.
- Prior work in acquisition analytics, segmentation, marketing science, or customer/agent lifecycle analytics.
- Familiarity with CRM systems, lead management tools, or marketing automation platforms.
- Understanding of acquisition funnel analytics, lead scoring, and conversion tracking.
Education
- Bachelor’s degree in Computer Science, Statistics, Mathematics, or a related quantitative field.
- Master’s or Ph.D. preferred.
About Integrity
Integrity is one of the nation’s leading independent distributors of life, health and wealth insurance products. With a strong insurtech focus, we embrace a broad and innovative approach to serving agents and clients alike. Integrity is driven by a singular purpose: to help people protect their life, health and wealth so they can prepare for the good days ahead.
Integrity offers you the opportunity to start a career in a family-like environment that is rewarding and cutting edge. Why? Because we put our people first! At Integrity, you can start a new career path at company you’ll love, and we’ll love you back. We’re proud of the work we do and the culture we’ve built, where we celebrate your hard work and support you daily. Joining us means being part of a hyper-growth company with tons of professional opportunities for you to accelerate your career. Integrity offers our people a competitive compensation package, including benefits that make work more fun and give you and your family peace of mind.
Headquartered in Dallas, Texas, Integrity is committed to meeting Americans wherever they are — in person, over the phone or online. Integrity’s employees support hundreds of thousands of independent agents who serve the needs of millions of clients nationwide. For more information, visit Integrity.com.
Integrity, LLC is an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender identity, national origin, disability, veteran status, or any other characteristic protected by federal, state, or local law. In addition, Integrity, LLC will provide reasonable accommodations for qualified individuals with disabilities.
