Applies developed subject matter knowledge to solve common and complex business issues within established guidelines and recommends appropriate alternatives. Works on problems of diverse complexity and scope. May act as a team or project leader providing direction to team activities and facilitates information validation and team decision making process. Exercises independent judgment within generally defined policies and practices to identify and select a solution. Ability to handle most unique situations. May seek advice in order to make decisions on complex business issues.
- Mines data using modern tools and programming languages.
- Defines and implements models to uncover patterns and predictions creating business value and innovation.
- Works with the business to understand the business domain perspective.
- Effectively tells stories with the data using visualization tools/methods to demonstrate insight impact and business value.
- Assures accuracy, integrity, and compliance of cleansed data.
- Maintains proficiency within the data science domain by keeping up with technology and trend shifts.
- Leads a project team of data science professionals
- Collaborates and communicates with project team regarding project progress and issue resolution.
- Represents the data science team for all phases of larger and more-complex development projects.
- Provides guidance, training and mentoring to less experienced staff members.
Knowledge & Skills
- Understanding of how to manage disparate unstructured and structured data in a distributed environment.
- Experienced in structured and unstructured data and modern data transformation methodologies.
- Ability to create advanced analytics models to pull valuable insights from data.
- Create stories and visualizations to describe and communicate data insights.
- Ability to use creativity to spot trends and tease out patterns in large datasets.
- Solid data modeling experience is required with proven application in applying Decision Trees, Regression analysis, Neural Network and other data mining techniques, experience with time series and experimental design.
- Ability to apply advanced statistical methodologies such as mixed model (random and fixed effects), simultaneous equations, time series based methods (ARIMA, Causal Autoregressive Mixed Models), neural networks, and multinomial discrete choice. Experience developing and implementing machine learning techniques in real time (e.g. API, PMML, Java, C, RPMML).
- Advanced hands on experience in Statistical Software (e.g. SAS, R, Python) and big data environments (e.g. cloud (e.g. AWS, Azure), and on-prem (e.g. Hadoop).
- Ability to comprehend and apply principles of advanced calculus, machine learning and advanced other statistical theory.
- Work effectively in cross-functional teams, having demonstrated strong partnerships with both internal and external business partners and alliances.
- Demonstrated ability to collect and organize data, work effectively with complex relational databases, conduct analysis and report on and apply results to "actionable insights/recommendations."
Scope & Impact
- Collaborates with peers, junior engineers, data scientists and project team.
- Typically interacts with high-level Individual Contributors, Managers and Program Teams.
- Leads a project requiring data engineering solutions development.
Education & Experience
- Master's or PHD degree in Mathematics, Economics, Physics, Computer Science, or equivalent.
- Typically 4-6 years' experience including graduate or postgraduate research.
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