Data Scientist

About The Role : Summary The Data Scientist will work in teams 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.



About The Role :

Roles and Responsibilities

As a Data Scientist, you will be part of a data science and cross-disciplinary team on commercially-facing development projects, typically involving large, complex data sets. These teams may typically include statisticians, computer scientists, software developers, engineers, services teams, solution architects, software architects, product managers, and end users, working in concert with partners in GE business units. Potential application areas include, but may not be limited to, remote monitoring and diagnostics across infrastructure and industrial sectors, process and operations optimization and asset management.

In this role, you will:

Develop analytics within well-defined projects to address customer needs and opportunities.

Work alongside data scientists, software developers and software engineers to translate algorithms into commercially viable products and services.

Work 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.

Share and discuss findings with team members.

Education QualificationBachelors Degree in Computer Science or STEM Majors (Science, Technology, Engineering and Math) with basic experience.

Desired Characteristics

Demonstrated skill in the use of one or more analytic software tools or languages (minimum:Python, optional:R)

Demonstrated skill at data cleansing, data quality assessment, and using analytics for data assessment

Demonstrated skill in the use of applied analytics, descriptive statistics, and predictive analytics on industrial datasets

Demonstrated awareness of using/applying/deploying GENAI in industrial settings

Demonstrated awareness of Advanced Process Control & Process Optimization in industrial settings

Technical Expertise:

Demonstrated awareness of feature extraction and real-time analytics methods

Demonstrated awareness of analytic prototyping, analytic scaleup, analytic scaling, and solutions integration

Domain Knowledge:

Demonstrated awareness of industry and technology trends in data science

Demonstrated awareness of customer and stakeholder management and business metricsLeadership:

Demonstrated awareness of how to function in a team setting

Demonstrated awareness of critical thinking and problem solving methods

Demonstrated awareness of presentation skills

Personal Attributes:

Demonstrated awareness of how to leverage curiosity and creativity to drive business impact