Senior Data Scientist

Divisions Maintenance Group - Cincinnati, OH

Full-time - Senior

Cincinnati, OH

Administrative and Support Services

About the position

As a Senior Data Scientist at Divisions Maintenance Group (DMG), you will play a pivotal role in building out the Marketplace Health and Pricing teams, focusing on establishing a robust Data Science practice. This position is integral to leveraging advanced analytic solutions that are expected to transform the industries in which DMG operates. You will be tasked with working on unique matching and pricing opportunities, utilizing your expertise to enhance the company's data science and software engineering capabilities. In this fast-paced, entrepreneurial environment, you will collaborate with various stakeholders to translate complex business challenges into actionable data science and advanced analytics solutions. Your responsibilities will include writing production-level code for analytics products, collaborating with data and software engineers throughout the product lifecycle, and applying a diverse range of analytical techniques such as predictive modeling, machine learning, and optimization. You will also be responsible for synthesizing and communicating your findings effectively to both technical and non-technical audiences, ensuring that your insights lead to thoughtful recommendations. Your role will require you to maintain a keen awareness of emerging data science techniques and technologies, particularly in the context of AI and machine learning, to continuously enhance the company's analytical capabilities. This position is based in either Cincinnati, OH, or Seattle, WA, and is designed for individuals who thrive in a dynamic and collaborative setting, eager to contribute to the growth and success of DMG's innovative initiatives.

Responsibilities

• Partner with stakeholders to translate complex business problems into data science and advanced analytics solutions.
• Write production level code for robust analytics products.
• Collaborate with data and software engineers to support data science solutions through the entire product lifecycle, including data wrangling, exploratory analysis, hypothesis testing, modeling, rapid prototyping, business validation and testing, and deployment.
• Leverage a diverse set of large and unstructured data to derive meaningful insights and information sets.
• Apply a variety of advanced analytical techniques including predictive modeling, machine learning, time series analysis, simulation, and optimization.
• Clearly and concisely synthesize and communicate findings to make thoughtful recommendations by combining business savvy with analytic rigor to technical and non-technical audiences.
• Maintain expertise and awareness of emerging data science techniques, technologies, and potential business applications for AI/ML.

Requirements

• Master's degree in an analytical field such as Data Science, Computer Science, Applied Mathematics, Operations Research or Economics (3 additional years of related experience may be substituted in lieu of a degree).
• 8+ years of relevant data science or software engineering experience developing and deploying production models and writing production code for analytics products.
• Experience working with a variety of statistical and modeling techniques including hypothesis testing, supervised learning (classification and regression), forecasting, unsupervised clustering, and optimization.
• Experience with Python and SQL including building python packages.
• Experience gathering, interpreting, and translating business requirements into analytical solutions.
• Demonstrated ability to communicate complex analytical concepts and results at multiple levels to technical and non-technical audiences.
• Experience with code version control platforms like GitHub, GitLab, or Azure DevOps.
• Experience working with data science and analytics teams to develop complex analytics products that have been successfully delivered to customers.
• Experience with large-scale data wrangling using databases or Spark.
• Knowledge of software engineering best practices for full software development life cycle, including coding standards, code reviews, source control management, continuous deployments, and testing.
• Experience working with docker containers.
• Experience working with APIs.
• Experience working with a UI or web framework.
• Ability to manage the stress of a fast-paced environment.
• Ability to meet the in-person requirements of the team and/or business needs.

Benefits

• Health, dental and vision coverage on day 1.
• Dollar-for-dollar 401K match up to 4% of salary with immediate 100% vesting.
• Paid Primary and Secondary Caregiver leave.
• Employee Assistance Program to assist with everyday challenges.
• Paid time off to volunteer.