Senior Data Scientist
Role details
Job location
Tech stack
Job description
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.
Requirements
Do you have experience in Data-driven problem-solving?, Do you have a Bachelor's degree?, 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., * 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., * 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.