Senior Data Scientist

About The Company
RIT Solutions, Inc. is a leading technology consulting firm dedicated to delivering innovative IT solutions tailored to meet the complex needs of diverse industries. With a strong focus on leveraging cutting-edge technologies, RIT Solutions partners with organizations to drive digital transformation, optimize operational efficiency, and foster data-driven decision-making. Our commitment to excellence and client satisfaction has established us as a trusted partner in the technology landscape, supporting businesses in achieving their strategic objectives through custom solutions and expert guidance.
About The Role
We are seeking a highly skilled Senior Data Scientist to join our team on a long-term contract basis. This remote position offers an exciting opportunity to work on complex and impactful projects within the insurance, hospitality, and travel industries. The ideal candidate will possess extensive experience in claims analytics, risk modeling, incident prediction, and fraud detection, with a strong emphasis on explainable AI techniques such as SHAP and LIME. The Senior Data Scientist will lead the development and deployment of advanced machine learning models, natural language processing applications, and optimization solutions that support enterprise risk management and operational decision-making.
This role requires a hands-on professional capable of translating business challenges into scalable data science solutions. Collaboration with cross-functional teams including Risk Management, Data Engineering, Data Governance, and MLOps is essential to ensure seamless integration and deployment of models. The candidate must be comfortable working with large, complex datasets and have proven experience in deploying production-grade AI systems that deliver actionable insights and measurable business value.
While local candidates to Chicago are preferred, remote work is fully supported for qualified applicants. The interview process involves a video interview to assess technical expertise and project experience. This position offers a unique chance to contribute to high-impact projects in a dynamic and innovative environment, shaping the future of risk analytics and operational optimization.
Qualifications
Minimum of 5 years of experience in Data Science, Machine Learning, Operations Research, or related fields, with at least 2 years of relevant experience supported by a PhD considered.
Proven expertise in claims analytics, insurance risk modeling, incident prediction, fraud analytics, and severity modeling.
Strong knowledge of explainable AI techniques such as SHAP and LIME.
Experience working within the hospitality and travel industries is highly desirable.
Hands-on experience with data governance, PII handling, data architecture, and enterprise data management tools.
Proficiency with Databricks, Snowflake, and NLP pipelines including text classification, LLM applications, and narrative analysis.
Expertise in operations research and optimization techniques, including linear programming, integer programming, mixed-integer programming, and familiarity with CPLEX and Gurobi solvers.
Solid programming skills in Python, SQL, and Spark for large-scale data processing and model development.
Experience deploying models into production environments with scalable architectures and agile delivery methodologies.
Responsibilities
Lead the design, development, and deployment of advanced machine learning and natural language processing models supporting enterprise risk management, claims analytics, and incident mitigation initiatives.
Develop optimization solutions utilizing linear, integer, and mixed-integer programming techniques to support resource allocation and decision-making processes.
Collaborate with cross-functional teams including Risk Management, Legal, Data Engineering, Data Governance, BI, and MLOps to ensure seamless integration of data science solutions into operational workflows.
Support large-scale data analysis across diverse datasets, including structured, semi-structured, and unstructured data sources, to extract actionable insights.
Build and validate predictive models for risk assessment, claim severity prediction, and fraud detection, ensuring accuracy and robustness.
Implement explainability techniques to provide transparent and interpretable AI solutions aligned with business requirements and compliance standards.
Support the development of NLP pipelines for narrative analysis, text classification, and LLM applications related to claims and incident reports.
Utilize mathematical optimization techniques and tools like CPLEX and Gurobi to solve complex operational challenges and support resource planning.
Document model development processes, maintain code repositories, and ensure models are scalable, maintainable, and deployable into production environments.
Stay current with emerging trends in data science, AI, and operations research, incorporating best practices into ongoing projects.
Benefits
RIT Solutions, Inc. offers a comprehensive benefits package designed to support the well-being and professional growth of our employees. This includes competitive compensation, flexible work arrangements, and opportunities for continuous learning and development. As a remote-first organization, we prioritize work-life balance and provide the necessary tools and resources to ensure our team members can perform at their best from anywhere. Additionally, we foster a collaborative and innovative work environment that encourages knowledge sharing, mentorship, and career advancement.
Equal Opportunity
RIT Solutions, Inc. is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate based on race, color, religion, gender, sexual orientation, gender identity or expression, age, national origin, disability, or any other protected status. We believe that a diverse workforce enhances our ability to serve our clients and innovate effectively, and we are dedicated to fostering a workplace where everyone can thrive.

Work arrangement
Yes