Bain & Company, Inc.

WHAT MAKES US A GREAT PLACE TO WORK

We are proud to be consistently recognized as 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 YOU’LL WORK WITH

Working alongside our generalist consultants, Bain's Advanced 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 YOU’LL DO

As a Lead, Machine Learning Engineer, you will lead on technical decision-making, embedded in projects and working with clients of different industries. You will also get your hands dirty writing code to get Machine Learning models working at real world production environments. This role teams up closely with Data Scientists, Impact Leaders, Consultants and Team Leaders to boost, deepen and streamline the development of innovative solutions that respond to high complexity problems.

ABOUT YOU

• Solid theoretical background on machine learning, and practical experience on building and deploying machine learning models.
• Write code in Python, embracing good code practices.
• Being able to deal with different tasks during the whole Machine Learning life cycle. What kind of tasks? ML model deployment and maintenance, building and using tools for ML monitoring, CI/CD pipeline design, supporting experimentation with ML models, designing and building data pipelines, among others.
• You have experience working with cloud infrastructure.
• You are comfortable with the lifecycle of a Machine Learning model.
• You are comfortable with Containers.
• You can build a service that exposes a ML Learning model to be consumed by other applications.
• You love teaching others and sharing good practices.
• You like getting your hands dirty with new tools and languages. Sometimes it is better to take a risk and learn something new, rather than choosing the good old hammer you always use. It doesn’t matter if you take more time, it is an investment for the future.
• You like being versatile. You get bored when every day looks the same, so you like sometimes getting dressed as a Data Scientist, Data Engineer or Software Engineer.
• Constant collaboration with your teammates.
• Provide and accept frequent feedback.
• Be autonomous within a collaborative environment.
• Find the best and unique version of yourself and boost it!
• You have 5 or more years of experience and/or a relevant graduate degree.

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. Since our founding in 1973, we have measured our success by the success of our clients, and we proudly maintain the highest level of client advocacy in the industry.