Data Science Manager manages the daily activities of the team responsible for identifying business trends and problems through big data analysis. Oversees the interpretation of results from multiple sources using a variety of techniques, ranging from simple data aggregation via statistical analysis to complex data mining. Being a Data Science Manager manages the design and implementation of big data solutions for the organization. May require extensive knowledge of big data tools like Hadoop, Hbase, Hive, Zookeeper, etc. Requires a bachelor’s degree in related area. Additionally, Data Science Manager typically reports to senior management. The Data Science Manager manages subordinate staff in the day-to-day performance of their jobs. True first level manager. Ensures that project/department milestones/goals are met and adhering to approved budgets. Has full authority for personnel actions. To be a Data Science Manager typically requires 5 years experience in the related area as an individual contributor. 1 – 3 years supervisory experience may be required. Extensive knowledge of the function and department processes.
Data Science Manager Job Description Template
Our company is looking for a Data Science Manager to join our team.
Responsibilities:
- Building machine learning models, specifically natural language processing models, in Python, to develop insights for the business;
- Effectively delivering data to management to provide insight into solving the biggest problems in the company;
- Advanced machine learning modelling applied to large messy data sets using Python;
- Developing natural language processing products, in Python, for clients to provide solutions to their challenges;
- Providing innovative approaches and solutions;
- Providing actionable insight to the wider business;
- Kick start the acquisition of customers through both online and offline methods;
- Work with large data sets on advanced analytic projects;
- Creation and delivery of customer-first data science-driven through action;
- Be able to translate data and speak to non-technical people about your decisions and recommendations;
- Establishing and spotting opportunities for advocating data science techniques.
Requirements:
- Propensity modelling;
- Understanding of statistical and machine learning applications for general insurance;
- Experience of working with cloud infrastructure preferred;
- Data curiosity to understand problems and surface interesting facts;
- Ability to explain and articulate technical concepts to specialist and non-specialist audiences;
- Proficiency in using Python, R and other relevant programming languages;
- Strong team player who is able to work with people and deliver on projects by taking ownership;
- Machine Learning;
- Proven track record of embedding data science solutions in a commercial context;
- Python or R;
- Highly dedicated and committed to delivering quality output by working to deadlines;
- Strong interpersonal skills;
- Innovative approach to solving business problems using data.