Location(s): United States ; Massachusetts; Boston
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. GE offers a great work environment, professional development, challenging careers, and competitive compensation. GE is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other characteristics protected by law.
Role Summary: The Principal Data Scientist will be a key member of the Data Analytics and Machine Learning team that will be responsible for curating and analyzing large sets of business and operations data of GE’s customers across several industry verticals.
Essential Responsibilities: This role will be responsible for analyzing the data and creating descriptive and predictive feature models. They will also very closely work with Subject Matter Experts and Business Analysts to rapidly understand the domain and iteratively refine the analyses and models to create high-fidelity automated analytics solutions.
Work closely with Subject Matter Experts to gain deep understanding of various business and operations related data sets
Participate in data science workouts to shape data science opportunities and identify opportunities to use data science to create customer value
Guide junior members to develop, verify, and validate analytics to address customer needs and opportunities.
Guide cross-functional teams to translate algorithms into commercially viable products and services.
Investigate and apply data analytics and machine learning techniques to create data summaries, identify cause-effect analysis across disparate data sources, and create high-fidelity prediction models for various business KPIs.
Guide and otherwise contribute to technical teams in development, deployment and application of applied analytics, predictive analytics and prescriptive analytics.
Work with the engineering team to incorporate your analyses and solutions, including working with the visualization team to create intuitive UI and rich UX stories.
Partner with data engineers on data quality assessment, data cleansing and data analytics efforts
Generate reports, annotated code, and other projects artifacts to document, archive, and communicate your work and outcomes.
Communicate methods, findings and hypotheses with stakeholders.
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