Sr Data Science Engineer

Compeer Financial is seeking collaborative, innovative and dynamic professionals to be a part of our Top Workplace culture!

Tell me more about this opportunity.

Position Overview:

This position is responsible for building analytics tools that utilize the data pipeline to provide actionable insights for decision making. The incumbent operationalizes and maintains machine learning models developed by data scientists/quantitative analysts within the organization to ensure that the machine learning models or data analytics work product developed by data scientists are efficiently transitioned into robust, scalable, and maintainable production systems.

Essential Functions:

• Develops data models, data pipelines and streamlines the deployment of models into production environments that could include machine learning.
• Builds and maintains pipelines for data analytics projects that include machine learning, enabling seamless integration and delivery of model updates.
• Monitors the performance and accuracy of projects in production, and performs regular maintenance to ensure they continue to meet business needs.
• Works closely with quantitative analysts to understand their models' requirements and provides the necessary infrastructure and tooling for model/data analysis training and experimentation.
• Optimizes the performance of data queries and machine learning models and the underlying infrastructure for speed, efficiency, and cost-effectiveness.

Minimum Qualifications & Required Knowledge, Skills and Abilities:

• Bachelor's degree in math, computer science, management information systems, or related field or an equivalent combination of education and experience sufficient to perform the essential functions of the job.
• Minimum of 7 years of experience with various MS SQL environments (2008, 2012, 2014, 2017, 2019), designing and implementing objects using SQL Server Data Tools.
• SQL Server and/or other Microsoft technologies, preferred.
• Advanced knowledge of Python, R, and/or Java, with an emphasis on Python due to its extensive use in machine learning and data science.
• Advanced experience with machine learning frameworks (e.g., PyTorch) and algorithms, as well as the ability to understand and interpret models created by data scientists.
• Advanced experience with cloud platforms such as AWS, or Azure, including services related to machine learning, computation, storage, and orchestration.
• Advanced knowledge of container management systems to deploy and manage machine learning models at scale.
• Ability to work with big data technologies and databases (SQL), as well as to preprocess and handle large datasets.
• Advanced communication skills to work effectively with cross-functional teams, including data scientists (quantitative analysts), and business stakeholders.
• Strong analytical and troubleshooting skills to resolve deployment issues and optimize model performance.
• Valid driver's license.

Who is Compeer Financial?

Compeer Financial exists to champion the hopes and dreams of rural America. By joining our team, you will help empower those in agriculture and rural communities to achieve their goals and expand their possibilities. We embrace business agility and innovative approaches to serving our clients and communities.

Why join our team?

• Amazing team members who are passionate about serving agriculture and rural America.
• Investment in our team members' education, growth and development.
• Engagement in our communities through giving back and volunteerism.
• Flexible, collaborative and dynamic work environment.
• Great benefits:
  • Medical, Dental, Vision insurance
  • 401K (3% Compeer contribution & up to an additional 6% match)
  • Paid time off (vacation, sick leave, holidays, volunteer time)

Find out why our team members choose Compeer Financial by watching this video .

How do I apply?

Qualified candidates, please apply online at www.compeer.com/careers .

Compeer Financial is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, or any other characteristic protected by law.