About Us: GE is the world's Digital Industrial Company, transforming industry with software-defined machines and solutions that are connected, responsive and predictive. Through our people, leadership development, services, technology and scale, GE delivers better outcomes for global customers by speaking the language of industry.
Role Summary: The Sr Staff Data Scientist will work in and lead teams as technical domain expert addressing statistical, machine learning and data understanding problems in a commercial technology and consultancy development environment. In this role, you will contribute to the development and deployment of modern machine learning, operational research, semantic analysis, and statistical methods for finding structure in large data sets. In this role you will be
Essential Responsibilities: Work with a team of Data Scientists & Engineers to solve business problems using analytics, typically involving large data sets. Work closely with Data Science leaders, functional leaders from Finance, Marketing, Risk and IT functions who come together to work on applying Data and Analytics to drive operational excellence. Potential application areas include - • -Responsible for Data science projects solutioning with broad analytics scope and high impact to the GE Power Generation Services •Responsible for leading, executing and operationalization of world class data driven methods, advanced algorithms and capabilities to support the needs of GE businesses • Driving Operational excellence by using Data Science to drive visibility, generate insights and suggest actionable solutions for different Enterprise Standards such as Sourcing, Sales, Services, Risk & Financial Operations • Implement/advocate new data science approaches and methodologies (ex. Neural Nets, Bayesian methods, SVM etc.) to improve operations and business outcomes • Communicate methods, findings, and hypotheses with stakeholders and articulate Data Science findings to a wide variety of business audience clearly & concisely. • Participate in both short and long term projects and maintain balance to deliver on business objectives • Initiate new ideas to develop effective value added products. • Effectively communicate with leadership and other various levels of the organization Develop new data sources needed for the solution of complex problems, integrates adjacent systems and data analytics capabilities. • Participate in defining integrated domain and statistical approaches and best practices. Perform discovery/exploratory development of new analytic algorithms/techniques to enhance existing commercial products and offerings. • Lead the development and deployment of modern machine learning, operational research, semantic analysis, and statistical methods for finding structure in large data sets. • Playing leading role in a data science or cross-disciplinary team on commercially-facing development projects, typically involving large, complex data sets. Following industry dynamics. Leverages knowledge about competitors, trends, and changing regulations across the broad environment to bring new ideas to the team. • Partner with Product Managers to shape Statements of Work for Data Science opportunities and GE Software Solutions. • Participate in shaping Data Science opportunities and identify opportunities to use data science to create customer value.; Lead in developing, verify, and validate analytics to address customer needs and opportunities. Lead as part of a cross-functional team to translate algorithms into commercially viable products and services. • Lead in technical teams in development, deployment, and application of applied analytics, predictive analytics, and prescriptive analytics. Perform exploratory and targeted data analyses using descriptive statistics and other methods. • Work with data engineers on data quality assessment, data cleansing and data analytics. Generate reports, annotated code, and other projects artifacts to document, archive, and communicate your work and outcomes. Communicate methods, findings, and hypotheses with stakeholders. Communicate and engage cross-functional teams •Utilizing your experience or expertise to solve problems, be responsible for work that is less defined in scope, have the ability to effect short-term and some long-term business goals
Qualifications/Requirements: Master’s Degree or PHD in Operations Research, Applied Statistics, Mathematics, Computer Science or in "STEM" Majors (Science, Technology, Engineering and Math) • Minimum of 8 years' experience working with Data Science • Minimum of 6 years’ experience with some/any of the following functions such as Finance, Risk, Service Operations, Commercial, Marketing and product management. • Minimum of 8 years’ experience using advanced data science methodologies and technologies such as Linear Regression, Logistic Regression, Optimization, Clustering, Survival Analysis, Decision Tree, Neural Networks, ARIMA etc. & tools such as Python, R, & SPSS & Other tools like Spark.
Desired Characteristics: • Passionate about Data Science and its implementation across several verticals • Familiarity with writing SQL Queries and working with databases, Data lake like Greenplum • Should be able to exercise high level of project involvement, demonstrate through data understanding and ownership • Ability to perform in a dynamic/high demanding business problems and objectives • Always open for new challenges and illustrate best possible solutions innovatively • Demonstrated ability to lead in a highly matrixed environment • Strong ability to communicate deep analytical results in forms that resonate with the business collaborators, highlighting actionable insights. • Inclination to discover novel opportunities for applying analytical techniques to business problems across the company • Ability to acquire any specialized domain knowledge required to be more effective in all required activities • Working knowledge of Mathematics, Statistics & Operations Research • Willingness to learn and develop critical data science skills • Willingness to work as team and contribute to the success of the project objectives
• Demonstrated skill in data management methods and analytic scaling • Demonstrated skill in prescriptive analytics and analytic prototyping • Demonstrated skill in solutions integration #DTR
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