Why MEC?

At Midwest Employers Casualty (MEC), we combine the stability of a Fortune 500 company with the agility of an innovative team. We are passionate about improving the quality of life for employees severely injured on the job and helping companies understand and mitigate risk. Our culture values collaboration, curiosity, and continuous learning. If you want to make an impact, work on meaningful projects, and grow your career in a supportive environment, MEC is the place for you.

Company URL: https://www.mecasualty.com

As a Senior Data Science Engineer, you’ll leverage our extensive data assets to deliver actionable insights and next-generation analytical products. You’ll work at the intersection of data engineering, machine learning, and AI, helping us build solutions that drive measurable business impact.

 

This role combines hands-on technical work with project leadership and mentorship responsibilities. You’ll design and improve application infrastructure, write production-quality code, support predictive modeling, and lead cross-functional projects. If you’re passionate about building scalable analytics solutions and mentoring others, we want to hear from you.

 

• Develop and deliver high-quality code, data analysis, and visualizations using best practices.
• Lead projects to automate analytical workflows and deploy predictive models.
• Engineer solutions for model development, testing, and deployment.
• Collaborate with Sr. Data Scientist to update or train new predictive models.
• Collaborate with internal and external stakeholders to provide analysis, reports, and data products.
• Define and maintain best practices for:
  • Using Azure and Databricks for data science.
  • Building and deploying generative AI applications                                                                                      
• Act as a liaison between Advanced Analytics and other technical teams across W.R. Berkley.
• Serve as a project lead, managing timelines, deliverables, and communication.
• Monitor production applications in Cloud and Kubernetes environments for performance and reliability.
• Mentor junior team members and promote knowledge sharing.

• 4–7 years in data science, software/ML engineering, or related roles. 
• 1–3 years building solutions with generative AI models. 
• 1–3 years developing AI solutions in Azure and/or Databricks. 
• Proficiency in SQL, Python, and Version control tools (GitHub, Bitbucket).
• Strong understanding of: 

1. Statistical and machine learning algorithms.
2. Natural Language Processing (NLP).
3. Deploying and scaling analytics solutions.

• Familiarity with:

1. ETL processes, data engineering, and data mining. 
2. Large-scale databases and data warehouses.
3. Docker and API development.

• Strong grasp of data visualization best practices. 
• History of leading technical projects using agile methodologies 
• Ability to communicate complex concepts clearly.
• Curious, self-motivated, analytical, and driven to solve complex business problems.
• Ability to manage multiple priorities under tight deadlines.
• Bachelor’s or Advanced degrees in data science, computer science, mathematics, statistics, engineering, physics, or other sciences (or college degree with significant technical experience in a corporate setting).
• Strong background in advanced mathematics, statistics, computer science, and/or data science.
  

We do not accept any unsolicited resumes from external recruiting agencies or firms.

The actual salary for this position will be determined by a number of factors, including the scope, complexity and location of the role; the skills, education, training, credentials and experience of the candidate; and other conditions of employment.

Sponsorship not Offered for this Role