[ref. i6793922] Expert Senior Manager, Machine Learning Engineer - Bain & Company
WHAT MAKES US A GREAT PLACE TO WORK
We are proud to beconsistently recognizedas one of the world's best places to work, a champion of diversity and a model of social responsibility. We are a Glassdoor Best Place to Work and we have maintained a spot in the top four since its founding in 2009.We believe that diversity, inclusion and collaboration are key to building extraordinary teams. We hire people with exceptional talents, abilities and potential, then create an environment where you can become the best version of yourself and thrive both professionally and personally.
WHO YOULL WORK WITH
Working alongside our generalist consultants, Bain'sAdvanced Analytics Group(AAG) helps clients across industries solve their biggest problems using our expertise in data science, customer insights, statistics, machine learning, data management, supply chain analytics and data engineering.Stationed in our global offices, AAG team members hold advanced degrees in computer science, engineering, AI, data science, physics, statistics, mathematics, and other quantitative disciplines, with backgrounds in a variety of fields including tech, data science, marketing analytics and academia.
WHAT YOULL DO
As a member of the growing Data Science and Machine Learning (ML) Engineering team in Bains 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
Translate business objectives into data and analytics solutions and, translate results into business insights using appropriate data engineering and data science applications
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
Manage the development of re-usable frameworks, models and components
Drive best practices in machine learning engineering and MLOps
Develop relationships with external data and analytics vendors
Provide thought championing in state-of-the-art machine-learning techniques
Develop, deploy and support 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
Support AAG leadership in extending and growing 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 (30%)
Consideration will be given to individuals with a specialization in NLP or Computer Vision
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 without supervision 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 with core techniques of linear algebra (as relevant for implementation of ML models) and common optimization algorithms
Experience using distributed computing engines, e.g. Dask, Ray, Spark
Experience using big data technologies and distributed computing engines, e.g. HDFS, Spark, Kafka, Cassandra, Solr, Dask