Engineer Data Science

Mayer Brown is an international law firm positioned to represent the worlds major corporations funds and financial institutions in their most important and complex transactions and disputes. We are recognized by our clients as strategic partners with deep commercial instincts and a commitment to creatively anticipating their needs and delivering excellence in everything we do.

We are a collegial collaborative firm where highly motivated individuals with an unwavering commitment to excellence receive the opportunity support and development they need to grow thrive and realize their greatest potential all while supporting the Firms client service principles of excellence strategic partnership commercial instinct integrated strengths innovation and collaboration across our international firm.

If you enjoy working with team members whose defining characteristics are exceptional client service initiative professionalism responsiveness and adaptability you may be the person we are seeking to join our InformationTechnology department in our Chicago office as an Engineer: Data Science.

The Engineer: Data Science is responsible for the design development and delivery of advanced analytics and AI solutions in support of the firms Data and AI strategy. This role works closely with the data science team IT engineers and business teams to implement reliable scalable solutions that deliver measurable business value.

The Engineer applies experience in data science AI methods and modern engineering practices to build and deploy solutions in production environments. The role emphasizes delivery excellence ensuring that solutions are practical efficient and compliant with the firms standards for security confidentiality and governance. Working closely with data science IT and data teams the Engineer translates complex concepts into practical solutions that support critical business outcomes.

Essential Functions:

• Solution Delivery
  • Design build and deploy data science and AI solutions end-to-end from design and development through testing release monitoring and support.
  • Operationalize models with CI/CD pipelines automated testing and monitoring applying MLOps practices such as versioning retraining and drift detection (tools: MLflow Azure ML Databricks)
  • Leverage both open-source frameworks (LangChain Hugging Face etc.) and enterprise platforms (Azure OpenAI Databricks etc.) to deliver production ready scalable AI solutions
  • Implement generative AI and advanced analytics features including embeddings retrieval-augmented generation and building AI agents and chat-based solutions.
  • Write clean testable and well-documented code using modern engineering practices (unit testing code reviews API development Azure DevOps preferred).

• Technical Design & Architecture
  • Ensure solutions align with enterprise architecture data governance and security standards
  • Collaborate with enterprise architects IT and business stakeholders to validate approaches
  • Contribute to lifecycle management practices including model versioning monitoring and continuous improvement of delivery processes
  • Evaluate and pilot emerging technologies to improve scalability and solution quality

Education/Training/Certifications:

• Bachelors degree in Computer Science Data Science or a related field required
• Masters degree in Computer Science Data Science or a related field preferred

Professional Experience:

• 2-4 years of hands-on experience delivering data science machine learning or AI solutions in production environments
• Law firm or professional services industry experience a plus but not required

Certifications

• Microsoft Certified: Azure AI Engineer Associate Azure Data Scientist Associate (preferred)
• Databricks Certified or equivalent cloud ML platform certification (preferred)

Technical Skills:

• AI/ML solution delivery: Experience developing testing and deploying complex high-impact solutions into production ensuring reliability and scalability
• Cloud Platforms: Hands-on with Azure (preferred) AWS or GCP; familiarity with Microsoft Fabric/Synapse data lakehouse architectures and containerization (Docker/Kubernetes)
• Frameworks: Proficiency with modern AI and ML frameworks such as PyTorch TensorFlow LangChain and enterprise AI platforms such as Azure OpenAI Service
• ML Ops practices: Strong understanding of CI/CD model versioning monitoring retraining and lifecycle management using cloud-based tools
• Generative AI: Applied experience with large language models (LLMs) embeddings retrieval-augmented generation (RAG) and building AI agents or chat-based solutions
• Data engineering alignment: Familiarity with data integration ETL and governance standards to ensure AI/ML solutions align with enterprise architecture

Performance Traits:

• Proven ability to work under pressure and manage multiple priorities meeting deadlines in a fast-paced environment with shifting priorities
• Strong written and verbal communication skills with the ability to communicate effectively and professionally at all levels of the firm including senior leadership technical teams and external vendors
• Ability to work in a diverse cross-functional team environment effectively supporting the demanding needs of a global law firm
• Must be a self-starter demonstrating a high level of initiative in problem-solving process improvement and driving data management best practices
• Strong customer service orientation anticipating stakeholder needs proactively addressing concerns and exercising independent judgment
• Exceptional attention to detail and organizational skills ensuring accuracy in documentation data integrity and process adherence across multiple projects
• Demonstrates strong strategic thinking and problem-solving skills analyzing complex data challenges and developing structured actionable solutions
• Ability to present complex data concepts to nontechnical stakeholders translating technical information into clear business-friendly insights
• Collaborate effectively across departments and organizational levels ensuring alignment between business needs IT capabilities and governance policies
• Strong analytical and problem-solving skills with a focus on delivering business value through data-driven solutions to enhance reporting data governance and decision making