Bain & Company is one of the world's best companies to work for (voted No. 1 on Glassdoor for 2017). Since our radical beginnings as a challenger of the status quo, our formula for success has been simple create a high-
impact, supportive culture where immensely talented people are encouraged to be brilliant at what they do.
We pride ourselves on hiring the best of the best we look for people who want to do great things; the learning curve is steep, and the exposure is energizing.
Our global offices share a diverse, informal environment where you’ll feel at home, regardless of the city you’re in and you’ll work alongside some of the top people in their field.
In return we offer a competitive salary, bonus and benefits (including laptop, phone, health insurance, lunch & travel contribution as well as non-
corporate dress code and state of the art offices). In addition, your professional development will be taken seriously from day one;
you will experience some of the most comprehensive training in the industry.
Our Advanced Analytics Group is a team of experts in data science, engineering, marketing science, operations research and primary research.
You will work alongside Bain’s consulting teams to provide high quality results for our clients, some of the most successful and pioneering businesses in the world.
You will also work to advance AAG’s and Bain’s analytic capabilities and provide training to the consulting staff as needed.
Provide data science services to Bain case teams and clients worldwide. You will work with 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 enviroments
Keep abreast of new and current statistical methodologies, machine learning and data wrangling techniques.
Where appropriate, train other team members to support the use of data analytics tools and to expand the use of machine learning within
Combine domain expertise to perform feature engineering
Proficiency in SQL is required, and familiarity with NoSQL data stores is a plus
Proficiency with data wrangling, visualization and modeling in either R or Python is required, familiarity with other analytical software such as SAS or SPSS is a plus.
Experience with explaining and performing a variety of data science and machine learning techniques
Examples of domain expertise in which we are interested is : predictive modeling, churn analysis, time series forecasting, computer vision, text mining, recommender systems, market basket analysis, segmentation, graph analytics, natural language processing and text analytics
Experience with dashboard and reporting tools such as Tableau and Qlik
Experience with deep learning tools such as Keras, TensorFlow or Theano is a plus.
Experience with distributed computing frameworks such as Hadoop and Spark is a plus
Experience with Git and modern software development workflow is a plus
Strong interpersonal and communication skills are a must.
Ability to explain and discuss mathematical and machine learning technicalities to a business audience.
Must thrive in a fast paced environment and be able to work independently
Fluent in German and English