Data Science Specialist

GE Aviation

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Bengaluru, Karnataka, India2 weeks ago

Job Description

As a Data Science Specialist, you will be part of a cross-disciplinary team working on commercially-facing development projects involving massive, complex data sets. These teams include statisticians, computer scientists, software developers, engineers, and product managers working in concert with partners in GE business units. Potential application areas include remote monitoring and diagnostics across industrial sectors, operations optimization, and financial portfolio risk assessment.
You will play a critical role in addressing customer needs by developing applied, predictive, and prescriptive analytics. Working closely with data engineers and software developers, you will perform data quality assessments, translate algorithms into commercially viable services, and generate annotated code and project artifacts to document your outcomes.

Algorithm Development: Develop applied analytics, predictive analytics, and prescriptive analytics within well-defined projects to address customer opportunities.
Commercial Translation: Work alongside software developers and engineers to translate complex algorithms into viable, commercial products and services.
Data Analysis: Perform targeted and exploratory data analyses using descriptive statistics and advanced ML methods.
Data Quality: Collaborate with data engineers on rigorous data quality assessments, data cleansing, and pre-processing.
Reporting: Generate comprehensive reports, annotated code, and other artifacts to archive and communicate project outcomes.
Cross-Functional Collaboration: Actively share and discuss analytical findings with team members and global stakeholders.

Education: B.Tech / B.E. or an equivalent Bachelor’s degree in Artificial Intelligence, Machine Learning, Computer Science, Applied Statistics, or a related technical field.
Programming Proficiency: Absolute proficiency in Python is mandatory.
Generative AI: Demonstrated skill and hands-on experience in implementing GenAI solutions (including fine-tuning, prompt engineering, and leveraging pre-trained models).
Cloud & ML Platforms: Familiarity with major cloud platforms (e.g., AWS, Azure) and unified analytics platforms like Databricks, along with their native AI/ML services.
Data Handling: Demonstrated skill in data quality assessment, robust cleaning, pre-processing, and leveraging AI/ML methods for solving real-world business problems.
Soft Skills: Strong communication, storytelling through data visualization, and a problem-solving mindset. Must be collaborative and act as a change-agent within cross-functional teams.

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