This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description The Data Scientist is responsible for applying advanced analytics, statistical modeling, and machine learning techniques to support strategic decision-making across the organization. This role partners closely with stakeholders in Underwriting, Actuarial, Claims, Product, Revenue, and Customer Experience to translate business questions into analytical solutions that improve operational performance, risk evaluation, and customer outcomes. - Develop predictive models, explore new data sources, and generate actionable insights that support pricing, underwriting, claims management, and operational efficiency. - Contribute to the development and operationalization of models and analytics solutions by working with engineering and product teams to integrate insights into business tools, dashboards, and workflows. Qualifications - Bachelor's degree in data science, Statistics, Mathematics, Computer Science, Economics, or a related quantitative field required. - Advanced degree (MS or PhD) preferred. - 3 - 7 years of experience in data science, advanced analytics, or statistical modeling roles. - Experience working with large datasets and complex analytical problems. - Strong programming skills in Python and SQL. - Experience with statistical modeling and machine learning techniques. - Experience with data visualization and analytical tools (e.g., Tableau, Power BI, Looker, or similar). - Ability to translate complex analytical findings into clear business insights. - Strong problem-solving and critical thinking skills. - Ability to collaborate effectively with both technical and non-technical stakeholders. Requirements - Partner with stakeholders across Underwriting, Actuarial, Claims, Product, and Revenue to identify opportunities where data can inform better business decisions. - Translate business questions into analytical frameworks, hypotheses, and statistical approaches. - Analyze customer, broker, and operational data to identify trends, anomalies, and opportunities to improve engagement, retention, and operational performance. - Conduct exploratory data analysis to investigate business problems and generate actionable insights. - Communicate analytical findings through visualizations, dashboards, and written summaries. - Develop predictive models and statistical analyses to support pricing, underwriting, claims, reserving, and operational initiatives. - Apply machine learning techniques including regression, classification, clustering, and other statistical learning methods to solve complex business problems. - Evaluate model performance and continuously improve models based on new data and changing business needs. - Explore internal and third-party data sources to enhance model performance and uncover new insights. - Collaborate with engineering and product teams to deploy analytical models into production systems and operational workflows. - Support the implementation of MLOps practices, including model versioning, deployment pipelines, monitoring, and lifecycle management. - Monitor models for performance degradation, bias, or drift and implement improvements as needed. - Document model assumptions, methodology, and validation processes to support transparency and governance. - Contribute to the improvement of internal data infrastructure, ETL pipelines, and reporting architecture. - Support the development and optimization of dashboards and analytics tools used by business teams. - Ensure data quality, consistency, and reliability across analytical workflows. - Identify opportunities to automate recurring analyses and reporting processes. - Work closely with business stakeholders to ensure analytics solutions align with operational needs and strategic objectives. - Partner with product and engineering teams to integrate analytical capabilities into internal platforms and decision tools. - Provide analytical support for ad-hoc requests and strategic initiatives. - Other duties as assigned. Benefits - Flexible PTO - Generous parental and caregiver leave - 401K match - Excellent medical, dental, and vision plans - Remote-first culture - Annual $1000 tuition reimbursement stipend - And more!

• Translate business requirements into technical specifications, data models, data streams, and databases • Develop production ready geospatial workflows and data pipelines using open-source python libraries • Work with online transaction processing (OLTP) and online analytics processing (OLAP) stacks (PostgreSQL, DuckDB, PyArrow, Parquet / GeoParquet) • Develop spatial computation with H3, Shapely, GDAL/OGR and other lightweight geospatial utilities • Write testable, benchmarked code using pytest and async test patterns • Build with python package managers like uv and poetry utilizing pyproject.toml for project management • Collaborate in open-source–style repositories with linting, formatting, typing, and CI expectations • Build CI/CD pipelines with integrated unit tests • Convert or embed ML/AI workflows into production-grade, enterprise systems • Utilize Research, Plan, Implement strategies for AI-driven development practices • Design, develop, and maintain infrastructure for geospatial analysis and ML/AI applications on large data.

About the company: Seek, an Eldridge company, is on a mission to connect analytics developers and consumers like never before - driving business value in minutes, not months. Insight Cloud, the analytics app store for your business, was created to make it easy for everyone to build, distribute, and consume data & analytics apps in the thriving cloud analytics economy. Insight Cloud delivers instant access to curated, ready-to-use analytics apps from the leading providers in the market, accelerating your speed to insights by 15X+ while eliminating the pain of building, hosting, and maintaining an entire analytics ecosystem on your own. Built for developers and consumers alike, Insight Cloud is not just another tool to work with data - it is the platform connecting leading analytics developers with innovative consumers - driving business value faster than ever. About the role: Seek’s Data Science team is central to our mission making advanced predictive analytics and machine learning applications accessible to businesses of all sizes.  Your work will involve exploring customer and partner data sets, developing predictive models, and applying machine learning techniques to uncover trends, patterns, and insights that can generate significant improvements to industry-wide practices. You will collaborate closely with stakeholders to build and launch new analytics apps, ensuring that the insights generated are accessible through Seek’s app store. In this role you’ll get to: - Analyze large (and sparse) datasets to extract meaningful patterns, trends, and insights using advanced statistical methods and machine learning algorithms.  - Construct and maintain data processing workflows, ensuring efficient mapping and transformation of client source data.  - Perform data enrichment by sourcing additional datasets and integrating them with client data to enhance analytical depth and accuracy.  - Develop complex SQL queries and Python scripts to transform and model data, tailoring configurations and fine-tuning parameters for optimal performance.  - Translate business challenges into analytical frameworks, proposing and implementing data-driven solutions that have a tangible impact on our clients’ decision-making processes.  - Create and maintain interactive dashboards that provide intuitive visualizations of data insights, enabling users to derive clear, actionable information.  - Work closely with analytics engineers, other data scientists and business stakeholders to ensure that ML models are aligned with business goals and technical requirements. - Write clear and comprehensive documentation for ML models, pipelines, and workflows to facilitate collaboration and reproducibility. Qualifications: - 5+ years of experience in data science, with a proven track record of deploying and training machine learning models - Advanced proficiency in Python ML libraries such as Scikit-learn, TensorFlow, and PyTorch for regression, classification, clustering, and deep learning techniques - Strong understanding of gradient boosting frameworks such as XGBoost and LightGBM for building high-performance models - Strong expertise in data and feature engineering including data cleaning, normalization, transformation, and creating/selecting relevant features from raw data - Strong expertise working with large-scale datasets directly within cloud data warehouses such as Snowflake, DataBricks, or Redshift - Advanced SQL skills: joins, subqueries, window functions, common table expressions (CTEs), aggregations, complex string manipulations, stored procedures and functions - Bachelor's degree in data science, statistics, computer science, or a related field. We’re especially interested in you if you have: - Experience with SnowPark ML (Snowflake) for Python: DataFrame API, user-defined functions (UDFs), and ML Pipelines - ML performance optimization experience: efficient computation, parallel processing, hyperparameter turning, model pruning, and quantization - Experience with data visualization tools and techniques - Excellent problem-solving and creative thinking skills with ability to drive complex data analysis and development forward independently - Strong communication skills with the ability to present data and articulate complex technical concepts clearly and concisely   Benefits: - Medical Insurance, Dental Insurance, PTO, 16 annual company holidays, 401K, Vision Insurance Tools we use: - SQL, Python ML, Scikit-learn, TensorFlow, PyTorch, Snowflake, DataBricks, Redshift Salary - The annual salary range for this position is between $145,000 - $175,000, depending on experience and qualifications. Location - This is an entirely remote position for candidates based in the US. No Visa Sponsorship Available - We do not offer visa sponsorship at this time. What Sets Us Apart Seek is committed to a culture that values ownership, flexibility, and collaboration. We prioritize work-life balance and encourage our team to explore new ideas, test hypotheses, and innovate continuously. You’ll join a diverse group of professionals dedicated to pushing the boundaries of business analytics development, with ample opportunities to grow alongside talented peers who value your expertise and vision

• Design/improve workflows to create data for AI/ML training and evaluation • Dive deep into existing workflows and processes to gather data and insights • Critically assess annotation tooling and workflows • Quantitatively analyze large datasets, perform statistical analysis, calculate metrics, and make recommendations to improve accuracy and performance • Work closely with client stakeholders on understanding goals, gathering requirements, proposing solutions and executing them.