Leverage advanced data analytics to derive insights and optimize credit strategies. Partner with Engineering on building effective risk model and credit risk capabilities. Monitor portfolio as well as macroeconomic trends impacting loan performance. Drive adjustments to underwriting and marketing strategies to mitigate risk. May telecommute. Supervises direct reports.
Develop production data science applications in Python and design new AI services from scratch. Maintain and enhance current data science pipelines in complex high-load applications and collaborate closely with R&D and DevOps teams. Research, invent and adapt machine learning algorithms for dedicated business needs, perform predictive and statistical modelling, and perform ad-hoc analyses as required.
This contract is based on a 6 month, ∼40-hour per week contract with the potential to convert to a full-time, salaried employee status (with full benefits) based on performance and business needs. Reporting to the Director of Data Science, in this role you'll build machine learning models that directly drive customer acquisition and lending decisions.
Collaborate with product managers and stakeholders to define AI and machine learning objectives, requirements, and timelines. Design, develop, and implement AI models, algorithms, and applications to solve complex business challenges. Manage the end-to-end AI model lifecycle.
A Machine Learning Researcher researches, develops, and implements machine learning models to improve internal business operations, further analytical understanding, and/or create useful features to enhance Topstep’s product. MLEs will create reports, dashboards, and/or data-centric tools. This includes data gathering, cleaning, and validating phases, as well as exploration, analysis, feature engineering, training and model selection, launching, monitoring, and fine-tuning.
Ensure AI models remain accurate and continuously improved to meet business and compliance requirements. Leverage data science methods to drive insights and improve performance for informed decision-making. Responsibilities include fine-tuning AI models, monitoring outputs, and developing strategies for handling bias and compliance issues.
Help define and drive Rad AI's next generation of applied research in NLP and clinical AI. Collaborate closely with clinicians, engineers, and product leaders to translate foundational research into production-scale systems that improve outcomes for doctors and patients alike.
This Data Scientist II will be responsible for building and operationalizing statistical models, ML/AI solutions, and interactive dashboards to support strategic workforce planning and operational decision-making in the telehealth space. This role focuses on using data science to optimize workforce resource allocation and forecasting across a variety of business domains at Equip.
This position is central to delivering on our key activities of customer engagement and distribution through the creation of AI driven marketing optimization processes. This role will focus on increasing the efficacy of our Direct Mail process by delivering a new suite of ML models ranging from propensity models to LTV models. This role will be crucial in reducing our reliance on affiliate partners through expanding our customer base in non-affiliate channels.
Design end-to-end AI architectures, including data pipelines, model development, deployment, monitoring, and integration into enterprise systems. Leverage modern AI/ML frameworks and platforms. Ensure solutions follow best practices for scalability, reliability, and responsible AI. Partner with client stakeholders to understand business challenges and translate them into AI-driven solutions. Provide technical leadership in workshops and architecture design sessions.