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. We are committed to building a diverse and inclusive team and encourage candidates of all backgrounds to apply. Bain offers comprehensive benefits and flexible policies that are designed to support you, so you can thrive personally and professionally.
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 member of the Data Science and Machine Learning Engineering guild in Bain’s Advanced Analytics Group you will work alongside Bain’s consulting teams to deliver market-changing machine learning and generative AI solutions to our clients, some of the most successful and pioneering businesses in the world. In this role you will:
Provide data science services to Bain case teams and clients worldwide. You will work with other data scientists and case teams to assess client demands and suggest data science methods that provide practical, value-added answers to the client and case teams.Develop solutions that bring critical insights to wide scale of different problems such as targeting customers and segmenting markets, product design, marketing optimization, demand forecasting and brand valuation, profit and price analyses, and fraud detection.Develop, prototype and test machine learning algorithms on data sets that can range from a few data points to billions.Apply machine learning and statistical techniques including regression models, decision trees, random forests, gradient boosting, support vector machines, clustering and topic models.Prepare various sources of data using data wrangling methods in Python, R and SQL, leveraging infrastructure including Cloud computing solutions and relational database environments.Keep abreast of new and current statistical methodologies, machine learning and data wrangling techniques.ABOUT YOU:
Preferred: a Master’s Degree or Ph.D. in in a quantitative discipline such as Statistics, Mathematics, Engineering, Computer Science, or similar numerate and computational fields. 1-3 years relevant post graduate experience in applications of Data Science or equivalentStrong foundation in machine learning and statistics, including supervised and unsupervised algorithms, and Bayesian inference Good understanding of the principles of Responsible AI, particularly fairness, explainability and data privacy.While we are looking for genuinely creative problem solvers who can think outside the box, the following domains are typically of interest: generative AI, predictive modeling, time series forecasting, recommender systems, anomaly detection, pricing analytics, marketing analytics, customer analytics, and graph analytics.Experience in generative AI, including large language models, prompt engineering, and frameworks such as langchain.Proficiency with data wrangling, visualization and modeling in Python is required, and proficiency in at least one of Keras, PyTorch or Tensorflow is preferred.Exposure to either AWS, GCP or Azure, with some experience of deploying Python based solutions on cloud platformsExperience with Git, CI/CD, docker and modern software development workflow at the level required for modern ML development is requiredProficiency in SQL or equivalent NoSQL system is a plusStrong interpersonal and communication skills are pre-requisite for this role, especially in explaining complex technical issues to a business audience, due to a career path with increasing exposure to clientsThere may be significant travel requirements (up to 30%) due to the international nature of our business