Senior Associate, Data Science

Key Skills

Apache Hadoop, AWS, Azure, Big Data Technology, CUDA/GPU programming, Data science techniques, Deep Learning, Google Cloud Platform (GCP), Java Programming, Keras software library, Large data sets, PySpark, Python Programming, PyTorch, R Programming, SPARK Programming, SQL, TensorFlow

Job Description

This is an opportunity to be a part of Bain’s expanding Advanced Analytics Group (Bain’s team of data science, engineering, marketing science, operations research and primary research experts). Responsibilities include:

• 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 analytics solutions to the client and case teams.
• Design, develop and implement innovative analytics solutions to a wide scale of problems such as targeting and acquiring customers, segmenting markets, product design, marketing optimization, demand forecasting, 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 big data transactional volumes. Apply knowledge of statistics, machine learning, programming, and data modeling to recognize patterns, identify opportunities, pose business questions and make valuable discoveries.
• Align data and analytics outputs to meet business objectives. Clearly define business success criteria and target KPIs that the analytics solution can help achieve.
• Apply techniques including regression models, decision trees, random forests, gradient boosting, support vector machines, clustering and NLP/topic models. Able to identify appropriate variables to design the modeling approach, develop and validate the model.
• Drive exploratory data analysis from high-dimensional data sets. Execute data wrangling on various sources of structured or unstructured data. Perform necessary feature engineering techniques.
• Application of data prep and deploying analytics models on Python, R and SQL. Leverage cloud computing infrastructures, big data platforms and relational database environments.

ABOUT YOU

• 1-3 years of experience with data science machine learning, predictive modeling in a business or marketing science environment in large enterprises and deployments
• Domain expertise in machine learning & statistical modeling such as 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, etc. 
• Comfortable working with large, complex data sets from varying sources (e.g., transactional & enterprise data, unfiltered data sets, internet/public data or data science research). 
• Proficiency with data wrangling, visualization and modeling in either R or Python is required.
• Experience with deep learning tools such as Keras, TensorFlow, PyTorch, PySpark, MXNet is a plus.
• Experience with developing prototypes, actual models deployed in production or software development is a plus.
• Experience with tools in the distributed computing, GPU, cloud platforms and Big Data domains is a plus (e.g. HPC, GCP, AWS, MS Azure, Hadoop, Spark)
• Ability to bridge business context with technical details and explain and discuss mathematical and machine learning technicalities to a business audience. Good communication and presentation skills, both written and oral.
• Industry experience in retail, consumer products, financial services, TMT (tech-media-telco) is preferred but not required.
• Must thrive in a fast paced & collaborative environment
• Occasional travel pending on business needs
• Bachelor’s degree in Computer Science, Applied Mathematics, Econometrics, Statistics, Physics, Engineering, Data Science, Market Research or related field. Masters or Ph.D. degree would be a plus.
• Fluency in Korean required .