COMPANY PROFILE
Bain & Company is a global consultancy that helps the world’s most ambitious changemakers define the future.
Across 65 cities in 40 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. We earned a platinum rating from Eco Vadis, the leading platform for environmental, social, and ethical performance ratings for global supply chains, putting us in the top 1% of all companies. 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.
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. We are currently the top-ranked consulting firm on Glassdoor’s Best Places to Work list and have earned the #1 overall spot a record seven times.
Extraordinary teams are at the heart of our business strategy, but these don’t happen by chance. They require intentional focus on bringing together a broad set of backgrounds, cultures, experiences, perspectives, and skills in a supportive and inclusive work environment. We hire people with exceptional talent and create an environment in which every individual can thrive professionally and personally.
The Role
You’ll join our Data Science & Machine Learning Engineering experts within the AI, Insights & Solutions team. This team is part of Bain’s digital capabilities practice, which includes a group of experts in analytics, engineering, product management, and design. In this multidisciplinary environment, you'll leverage deep technical expertise with business acumen to help clients tackle their most transformative challenges. You’ll work on integrated teams alongside our general consultants and clients to develop data-driven strategies and innovative solutions. Together, we create human-centric solutions that harness the power of data and artificial intelligence to drive competitive advantage for our clients. Our collaborative and supportive work environment fosters creativity and continuous learning, enabling us to consistently deliver exceptional results.
Position Summary
As a Lead Data Scientist, you will leverage your experience to design, implement and refine advanced analytical and machine learning solutions across a wide range of industries. You will engage in the entire data science life cycle, focusing on developing and deploying impactful models and data-driven strategies at a production scale suitable for the world’s largest companies.
Essential Functions
- Develop data science and software solutions to address large-scale enterprise challenges for Bain's clients, serving as the data scientist and expert within a cross-functional team
- Develop and maintain long-lasting models, algorithms and tools that support internal or client needs
- Collaborate closely with and influence general consulting teams to identify analytics solutions for client business problems and to execute those solutions
- Collaborate with data science leaders to develop and advocate for modern data science concepts to both technical audiences and business stakeholders
- Collaborate with data engineering team to ensure data pipelines and platforms support modeling, experimentation and analytics use cases
- Transformations at scale, including cleaning, enriching, de-duping, joining, and correlated on structured, semi-structured, or unstructured data for modeling and analysis
- Define and implement new and innovative modeling techniques, experimentation strategies and analytics workflows within Bain full model development life cycle, including writing documentation, and unit/integration tests, and conducting reviews
- Support model deployment and operationalization in collaboration with engineering teams ensuring scalable data science solutions
- Collaborate with data engineering and analytics teams, and when needed, contribute to data acquisition, extraction, and preparation to ensure data is fit for modeling and analysis
- Establish and promote best practices for model development, documentation, and reuse, enabling scalable and repeatable approaches across industries and use cases
- Help prioritize and scope data science initiatives by translating complex client business problems into actionable projects with clear execution paths
- Provide technical guidance to external clients and internal stakeholders in Bain
- Contribute to industry-leading innovations that translate into great impact for clients in casework
- Stay current with emerging trends and technologies in data science, and proactively identify opportunities to enhance the capabilities of the analytics platform
Education
- Advanced degree in Computer Science, Engineering, Econometrics, Statistics or Information Sciences
- PhD is a plus
Experience
- 5 years minimum experience
- 3+ years of experience in analytics
Knowledge, Skills and Abilities:
Required
- Proficiency in Python with knowledge of data structures, algorithms, object-oriented design, testing and scalable code for machine learning workflows
- Experience deploying ML models using containerization using Docker, Terraform, and MLOps tools like MLflow and GitHub Actions
- Proficient in managing data workflows and pipelines for modeling (Airflow, Beam, Luigy, Spark, Nifi or any other)
- Working knowledge of SQL or NoSQL databases: PostgreSQL, SQL Server, Oracle, MySQL, Redis, MongoDB, Elasticsearch, Hive, HBase, Teradata, Cassandra, Amazon Redshift, Snowflake
- Experience with Cloud platforms and services (AWS, Azure, GCP, etc.)
- Experience scaling model training and inference on large datasets, and optimizing pipelines for performance in production environments
- Strong foundation in machine learning and deep learning, including supervised, unsupervised, reinforcement learning, NLP, and modern architecture
- Experience working according to agile principles
- Strong interpersonal and communication skills, including the ability to explain and discuss technicalities of solutions, algorithms and techniques with colleagues and clients from other disciplines
- Curiosity, proactivity and critical thinking
- Ability to collaborate with people at all levels and with multi-office/region team
- Professional knowledge of English and German is required
