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Lead Data Scientist

Institute of Electrical and Electronics Engineers
Piscataway, NJ Full Time
POSTED ON 2/22/2025
AVAILABLE BEFORE 5/20/2025

Description

Job Summary

The Lead Data Scientist architects and leads the development of state-of-the-art machine learning models and algorithms for large scale data and analytics applications for various types of datasets including structured tabular data, unstructured text, image, video, audio as well as numerical and measurement data for research, development, and product build. The Lead Data Scientist is an expert in the usage of complex data structures, algorithms, and advanced machine learning libraries to create innovative AI-driven products to address the rising demands of customers in science and technology domains. The Lead Data Scientist serves as a technical lead to Data Scientists and ensures the AI-driven models derived from the work of the Data Scientists meet the business customers and internal stakeholders' requirements. This position will report to the Director of Data and Analytics Product Engineering and may have one direct report.

Key Responsibilities

  • Design and lead the development of high-quality, low-latency, and cost-effective large-scale machine learning models for IEEE and non-IEEE data.
  • Lead model and algorithm design to derive business value and create new metadata from the analysis of large-scale datasets.
  • Design and lead the architecture and execution of machine learning models in feasibility and proof-of-concept stages.
  • Collaborate closely with Data and Machine Learning Engineers, and provide technical support and assistance on the transition of the models from feasibility and proof-of-concept stages to production stage.
  • Manages and provides technical directions to Data Scientists on data and analytics products and ensures the products meet the external customers' and internal stakeholders' requirements.
  • Passionately advocate for data and analytics capabilities and products and create a vision of success that can be vetted among colleagues to drive future success, articulates the vision, negotiates, persuades, and gains support for strategic initiatives that fit within the overall IEEE strategy.
  • Ensures analytics alignment and reliable engine output with internal and external stakeholders.
  • Keeps critical intellectual property (IP) and know-how about IEEE content within the organization.
  • Establishes partners and / or open-source technologies for data and analytics.
  • Works in conjunction with Publication Technology Operation Unit to create and manage analytic capabilities and products.
  • Collaborates in ongoing projects to deliver solutions used by our customers, volunteers, and other Operation Units.

Qualifications

Education

  • Master's or other advanced degree in Statistics, Mathematics, Computer Science, Engineering, or another quantitative field. Req
  • Ph.D. in Statistics, Mathematics, Computer Science, Engineering, or another quantitative field would be beneficial. Pref
  • Work Experience

  • 7-10 years Excellent understanding of data structures, algorithms, and advanced machine learning architectures including natural language processing, classification, transformers and deep learning architectures. Req
  • 4-7 years Expert hands-on experience in Python, Tensorflow, PyTorch, Pyspark, SQL and shell scripting or similar programming languages. Req
  • 4-7 years Expert hands-on experience in using cloud-based solutions and technologies for the development of machine-learning models. Req
  • Skills and Requirements

  • Excellent understanding of business requirements, translating them into model design and architecture, and implementing them in product build
  • Excellent debugging and code-reading skills.
  • Excellent Documentation and structured programming to support sustainable development.
  • Excellent management, communication and presentation skills
  • Ability to translate highly complex technical concepts to both technical team members as well as non-technical internal stakeholders and external customers
  • Ability to describe challenges and solutions in both technical and business terms.
  • Ability to develop and maintain excellent working relationships at all organizational levels.
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