Data Science Manager

Key Skills

Apache Hive, Big Data Technology, Data Analysis, Data pipelines, Data science techniques, Machine learning techniques, Neural Networks, Optimization, Python Programming, R Programming, Regression Analysis, Spark Core, SQL, Statistics

Job Description

Data Science Manager (Accenture LLP; Chicago, IL): Accenture LLP has multiple openings for the position of Data Science Manager in Chicago, IL, and the job duties are as follows:

• Address client’s business challenges by using big data and providing new insights from advanced predictive and optimization models.
• Collect big data from disparate data sources by interacting with the client’s IT team. Design models, algorithms, and visualizations that will help companies distill insights from huge volumes of chaotic data.
• Interpret analytical models, conduct analysis to gain insights into the root of the clients’ business problem, propose potential solutions to their problems, and assist in quantifying improvements in their metrics.
• Create high impact business strategies and roadmaps for solution implementation, to help clients reap the benefits of big data analytics on an ongoing basis.
• Supervise a team of analysts and consultants to gather data across multiple systems, and interpret clients’ problem and convert them into analytical solutions.
• Conduct project and issue management (status reporting, issue reporting, budget reporting) for assigned scope of work, and make decisions that impact the team through regular consultation with senior management.
• Adhere to strategic direction set by senior management. Interact with client and internal senior management on a regular basis.

Qualifications

BASIC QUALIFICATIONS:

Must have a bachelor’s degree in Computer Science, Technology, Computer Information Systems, Computer Applications, Engineering, Data Science, or related field, plus 5 years of progressive post-baccalaureate experience in the IT consulting industry.

Must have 3 years of experience in each of the following:

• Developing Machine Learning models including regression, classification, unsupervised learning, recommendation, and neural networks;
• Hyperparameter tuning and evaluation of Machine Learning models;
• Performing statistical analysis, data wrangling, exploratory data analysis, development and deployment of machine learning using Data Science tools including Python or R; and
• Utilizing SQL and Big Data tools including Hive and Spark to develop, deploy and optimize data engineering pipelines. 

Must have 1 year of experience applying statistical methods to business problems.

Must have willingness and ability to travel domestically approximately 80% of the time to meet client needs.