Expert Senior Manager, Machine Learning Engineering

WHAT MAKES US A GREAT PLACE TO WORK

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WHO YOU’LL WORK WITH

WHAT YOU’LL DO

As a member of the growing Data Science and Machine Learning (ML) Engineering team in Bain’s Advanced Analytics Group, you will:

- Collaborate closely with and influence business consulting staff and leaders as part of multi-disciplinary teams to assess opportunities and develop data driven solutions for Bain clients across a variety of sectors
- Partner closely with other engineering and product specialists at Bain to support development of innovative analytics solutions and products
- Transform existing prototype code into optimized scalable, production-grade software
- Lead the development of re-usable frameworks, model and components
- Drive best practices in machine learning engineering and MLOps
- Develop relationships with external data and analytics vendors
- Provide thought leadership in state-of-the-art machine learning techniques
- Develop and deploy industry-leading machine learning solutions, aimed at solving client problems across industry verticals and business functions
- Act as Professional Development Advisor to a team of 3-5 machine learning engineers
- Work closely with AAG leadership to extend and grow our machine learning, engineering and analytics capabilities
- Help develop Advanced Analytics intellectual property and identify areas of new opportunity for data science and analytics for Bain and its clients
- Travel is required

ABOUT YOU
- Advanced Degree in a quantitative discipline such as Computer Science, Engineering, Physics, Statistics, Applied Mathematics, etc.
- 10+ years of software engineering, analytics development or machine learning engineering experience
- 3+ years of experience managing data scientists and ML engineers
- Strong understanding of fundamental computer science concepts, software design best practices, software development lifecycle and common machine learning design patterns
- Solid understanding of foundational machine learning concepts and algorithms
- Broad experience deploying production-grade machine learning solutions on premise or in the cloud
- Expert knowledge of Python programming and machine learning frameworks (Scikit-learn, TensorFlow, Keras, PyTorch, etc.)
- Experience implementing ML automation, MLOps (scalable development to deployment of complex data science workflows) and associated tools (e.g. MLflow, Kubeflow)
- Experience working in accordance with DevSecOps principles, and familiarity with industry deployment best practices using CI/CD tools and infrastructure as code (e.g., Docker, Kubernetes, Terraform)
- Extensive experience in at least one cloud platform (e.g. AWS, GCP, Azure) and associated machine learning services, e.g. Amazon SageMaker, Azure ML, Databricks
- Familiarity with Agile software development practices
- Strong interpersonal and communication skills, including the ability to explain and discuss machine learning concepts with colleagues and clients
- Ability to collaborate with people at all levels and with multi-office/region teams
- Ability to work independently and juggle priorities to thrive in a fast paced and ambiguous environment, while also collaborating as part of a team in complex situations

ADDITIONAL SKILLS
- Proficiency in one or more of SQL, R, Java, C/C++, Scala, Rust, Go, Julia
- Experience using big data technologies and distributed computing engines, e.g. HDFS, Spark, Kafka, Cassandra, Solr, Dask

ABOUT US

Bain & Company is a global consultancy that helps the world’s most ambitious change makers define the future.

Across 64 cities in 39 countries, we work alongside our clients as one team with a shared ambition to achieve extraordinary results, outperform the competition, and redefine industries. We complement our tailored, integrated expertise with a vibrant ecosystem of digital innovators to deliver better, faster, and more enduring outcomes. Our 10-year commitment to invest more than $1 billion in pro bono services brings our talent, expertise, and insight to organizations tackling today’s urgent challenges in education, racial equity, social justice, economic development, and the environment