• Collecting data and using a wide range of data science techniques to uncover actionable insights or build analytics solutions • works autonomously within a specialized business management function • Provides seasoned specialized knowledge, advice and/or guidance to various stakeholders • oversees and/or independently performs tasks from end-to-end

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

• Owning end-to-end model development for pricing, demand forecasting, and elasticity estimation; productionizing models in Azure ML and Databricks • Implementing prescriptive analytics through optimization with Linear Programming, Mixed Integer Programming or Reinforcement Learning • Implementing and maintaining feature stores, model monitoring workflows, and drift checks using MLflow (metrics, alerts, lineage) • Designing and executing A/B tests or quasi-experiments to measure revenue, pricing uplift, and PCP attach rate impact • Applying SHAP/LIME and other model interpretability tools to explain drivers of model behavior to Revenue Management partners

• Build the next generation ML systems that transform the way people find what they love. • Focus on building, productionizing and scaling machine learning models, and promoting engineering excellence. • Work with data scientists and lead cross-functional collaboration with Strategy, Product, Merchandising, Marketing, and Engineering partners to enhance capabilities. • Drive step-change improvements in machine learning models through novel research, large-scale experimentation, and production deployment. • Improve how we serve real-time recommendations in production at scale.