The Data Scientist will be intricately involved in running analytical experiments in a methodical manner, and will regularly evaluate alternate models via theoretical approaches.The role will participate in the team's engagement with business stakeholders and partners to enhance the existing analytics solutions and develop new solutions to business problems.The role requires a thought leader that will be instrumental in providing inputs to the Data Science & Analytics Team for the design and building of predictive models and algorithms, exploratory data analysis, test design, statistical tests and measures, and business value measurement.Key accountabilities
- Evolve skills, solutions and the organization to predictive & prescriptive analytics
- Reporting and visualizations development to develop storytelling - using any of SSRS, Spotfire, PowerBI, realtime dashboarding, MI/BI and shallow analytics best practices.
- Deliver quality analytic solutions, combining science with the software development process and challenging current data science trends with new ideas and alternative methods
- Design and implement data analysis, data mining, research, analysis, and modeling strategies and best practices to internal clients
- Ownership of the development and delivery of data science solutions from concept to production
- Manages research targeted for innovations to solve business needs and technical challenges
- Serve as the subject matter expert to articulate areas such as strategic, business and data analytics & statistics, data science, big data, normalization and modeling
- Initiates data science based solutioning with a focus on revenue growth and achievement of the business' overall targets and objectives.
- Responsible for the preparation of documentation, presentations, and scientific based papers to communicate ideas to business leaders and executives.
- Personally, works on challenging fundamental data science issues where necessary, realizes, and develops solutions independently.
- In conjunction with Data Engineers, building and managing new data tables that support data collection, cross-functional data integration, data visualization, dashboards, predictive analytics, and data mining.
- Leverages data science tools and techniques in analyzing large data-sets that will enable development of custom models and algorithms to uncover insights, trends, and patterns in the data, which will be useful in availing informed courses of action.
- Create data science platforms to test and experiment with techniques inclusive of advanced analytics, behavioral modeling, and churn capitalizing on new data science approaches that can yield revenue for the business.
- Responsible for the evaluation of analytics and machine learning technologies in use in the business and communicates findings to key stakeholders through reports and presentations.
- Partners with other non-technical departments within the business assisting them in understanding how data science can benefit them and improve their effectiveness and performance.
- In collaboration with Data Engineers, Data Architects and Data Management, works closely with the IT department within the business for the purpose of facilitating easy and effective access to computing and data resources within the business.
- Takes initiative and stays up to date with the latest data science trends, techniques, and best practices, determining how to incorporate the most suitable practices in the department.
- Collaborative role with interaction with non-technical departments and, as such, will need to have exceptional communication skills in order to be able to tailor and convey technical messages in a clear and understandable manner, leading to business-wide improvement of data management, informed decision making, and ultimate improvement in performance.
- Enhancing data collection procedures to include information that is relevant for building analytic system
- A degree (Master's or PhD preferred) in Statistics, Machine Learning, Mathematics, Computer Science, Economics, or any other related quantitative field.
Essential experience and job requirements
- 3+ years of hands on experience in machine learning (supervised, unsupervised and ensemble methods), natural language processing or computer vision. Deep learning experience is a bonus
- Proven track record of developing, scaling and implementing these models in customer facing environments
- Strong programming skills: R, Python, Java etc along with stellar visualization and persuasive story telling
- Knowledge and exposure to cloud technologies, Azure and/or AWS.