Junior Data Science Engineer

Key Skills

Containerization, Continuous Integration & Continuous Delivery - CI/CD, Docker, FastAPI, Machine learning techniques, NumPy, Predictive Modeling, Python Programming, Scikit-learn

Job Description

The Junior Data Science Engineer role in the Customer Engineering team is an exciting opportunity to work at the intersection of AI/ML engineering, solution development, and go-to-market strategy. We are looking for a highly coachable, ambitious data science engineer who thrives in hands-on problem-solving and is eager to grow into a well-rounded AI/ML engineer.

Your work will focus on building reusable, production-ready AI solutions that accelerate customer adoption of the DataRobot platform. This means:

• Developing scalable, productionizable AI assets that customers can confidently integrate into their workflows.
• Ensuring AI solutions are resilient, maintainable, and easy to deploy, minimizing operational friction.
• Engaging with early-adopter customers and internal teams to refine and validate solutions.
• Collaborating with product, sales, marketing, and enablement teams to drive solution awareness and usage at scale.

Beyond developing and refining AI solutions, you will also help prioritize future investments by identifying high-impact opportunities and gathering customer feedback to refine existing assets.

This role is ideal for a highly motivated, coachable data scientist eager to work hands-on with Python, pandas, and modern AI tooling while making a real impact on customer success and AI adoption. If you thrive in a fast-paced, highly autonomous environment, enjoy solving complex problems, and want to build AI solutions that truly scale, we’d love to hear from you!

Key Responsibilities:

• Develop reusable, production-ready assets that accelerate AI/ML adoption for customers—ranging from demo environments to deployable templates.
• Prototype and experiment with AI/ML workflows using Python, pandas, and modern AI tooling, ensuring they are scalable and customer-ready.
• Implement and refine engineering best practices to improve performance, scalability, and maintainability of AI/ML solutions.
• Work within existing infrastructure to support scalable AI deployments, including CI/CD automation, API integrations, and containerized environments (Docker, Kubernetes).
• Contribute to, create, and maintain automated tests for AI/ML workflows.
• Collaborate cross-functionally with product, sales, and marketing teams to scale high-impact solutions.
• Work on real-world deployment challenges, including monitoring, logging, and improving reliability in AI/ML workflows.
• Support customer engagements by working directly with users to validate solutions, improve adoption, and ensure real-world impact.
• Stay ahead of industry trends, continuously refining our approaches and advocating for best practices in AI/ML engineering.
• Work closely with enablement teams to scale adoption of our solutions through documentation, content, and training materials.

Knowledge, Skills, and Abilities:

• Strong Python ecosystem knowledge with the ability to experiment, iterate quickly, and troubleshoot real-world ML workflows using libraries like pandas, NumPy, scikit-learn, and FastAPI.
• 1-5 years of experience in data science, machine learning, or AI development (or a top-tier CS/DS graduate with strong fundamentals).
• Highly coachable, adaptable, and eager to learn—we prioritize raw ability, curiosity, and work ethic over specific years of experience.
• Experience with ML model development, deployment, and evaluation—you should be comfortable turning data into insights and working with predictive models.
• Some familiarity with data engineering best practices, including working with structured/unstructured data, feature engineering, and optimizing ML pipelines.
• Proficiency in writing efficient, maintainable, and well-structured code, with an emphasis on reusability, scalability, and production readiness.
• Experience with software engineering best practices, including containerization (Docker), CI/CD automation, and cloud-based ML deployment.
• Ability to implement logging, monitoring, and debugging strategies to ensure the reliability and performance of AI/ML applications in production.
• Strong foundation in Computer Science fundamentals, including object-oriented design, data structures, and algorithmic problem-solving.
• Experience with APIs, SDK development, or ML platform integrations is a plus.
• Customer-facing or project-based experience is a plus, but we’ll help develop these skills.
• Self-motivated, driven, and eager to take on challenges—we’re looking for someone who thrives in a fast-moving, high-growth, and high-autonomy environment.

Nice to Have:

• Experience with cloud platforms (AWS, Azure, GCP) for AI/ML deployment.
• Some working knowledge of automated testing and test-driven development.
• Familiarity with CI/CD pipelines and DevOps practices.
• Basic knowledge of generative AI solutions like RAG, fine-tuning, etc.
• Master’s degree in Data Science or Software Engineering.

The talent and dedication of our employees are at the core of DataRobot’s journey to be an iconic company. We strive to attract and retain the best talent by providing competitive pay and benefits with our employees’ well-being at the core. Here’s what your benefits package may include depending on your location and local legal requirements:

• Medical, Dental & Vision Insurance
• Flexible Time Off Program
• Paid Holidays
• Paid Parental Leave
• Global Employee Assistance Program (EAP) and more!

DataRobot Operating Principles:

• Wow Our Customers
• Set High Standards
• Be Better Than Yesterday
• Be Rigorous
• Assume Positive Intent
• Have the Tough Conversations
• Be Better Together
• Debate, Decide, Commit
• Deliver Results
• Overcommunicate

Research shows that many women only apply to jobs when they meet 100% of the qualifications while many men apply to jobs when they meet 60%. At DataRobot we encourage ALL candidates, especially women, people of color, LGBTQ+ identifying people, differently abled, and other people from marginalized groups to apply to our jobs, even if you do not check every box. We’d love to have a conversation with you and see if you might be a great fit.