Senior Data Scientist

Role Description

Mitchell, an Enlyte company, is seeking an experienced Data Scientist to help us discover opportunities to drive customer and business value by leveraging AI/ML technology including generative AI and large language models, and guide product managers and engineers to realize the solutions within our broad range of products.

• Drive discovery of AI/ML opportunities across product portfolio and guide implementation.
• Design and optimize prompts for large language models to support generative AI features.
• Build, evaluate, and deploy machine learning models in production environments.
• Collaborate with product managers, engineers, and domain experts to translate business problems into technical solutions.
• Define best practices for ML pipeline automation, model monitoring, and scalable deployment.
• Communicate findings and recommendations to technical and non-technical stakeholders.

The successful candidate will be a self-starter, capable of driving the discovery process to tackle ambiguous problems alongside subject matter experts across business functions with minimal direction. This candidate will:

• Have excellent analytical skills and in-depth knowledge of machine learning methodologies, data and feature engineering.
• Be capable of providing insights to the engineering team in building scalable ML pipeline automation and defining best practices.
• Be an excellent communicator, capable of presenting findings to non-technical audiences and enjoy giving talks to expand the overall AI/ML knowledge of our organization.
• Demonstrate commitment to staying current with the latest research (through papers, public codebases, and blogs).

Qualifications

• MS/PhD in appropriate field (e.g. Math/Statistics/Computer Science) with 6+ (MS) / 3+ (PhD) years of professional experience in machine learning projects.
• 1+ years of experience in building, deploying and maintaining machine learning models on production environment.
• Experience in machine learning projects involving data warehouse, feature engineering, ML pipeline automation and ML monitoring.
• Excellent understanding of many machine learning algorithms/techniques/tools, capable of explaining the underlying concepts and principles.
• High proficiency with Python programming language.
• High proficiency with SQL.
• Good understanding of data warehousing and ETL techniques.
• Excellent written and verbal communication skills with the ability to educate and influence.
• High level of initiative and passion to deliver results.
• Experience with AWS Sagemaker is a plus.

Benefits

• Medical, Dental, Vision, Health Savings Accounts / Flexible Spending Accounts.
• Life and AD&D Insurance.
• 401(k).
• Tuition Reimbursement.
• An array of resources that encourage a lifetime of healthier living.
• Compensation depends on the applicable US geographic market. The expected base pay for this position ranges from $85,000 - $125,000 annually, based on skills, experience, and education.