Data Scientist with Graph Neural Networks AND Machine Learning

• We are seeking a highly skilled Data Scientist with proven expertise in Graph Neural Networks (GNNs) and Graph Machine Learning to lead the design, development, and implementation of graph-based AI models as part of a strategic Proof of Concept (POC).
• The GNN architecture is the core of this engagement and, therefore, candidates must demonstrate prior hands-on experience building, training, evaluating, and deploying graph-based machine learning solutions.
• General Data Science, Machine Learning, or Deep Learning experience alone will not be considered sufficient., * Design, build, and optimize Graph Neural Network (GNN) models for complex business problems.
• Develop graph-based solutions for:
• Link Prediction
• Node Classification
• Recommendation Systems
• Network Analysis
• Knowledge Graph Analytics
• Fraud Detection
• Entity Resolution
• Build scalable graph data pipelines and feature engineering workflows.
• Work with large-scale graph datasets and graph databases.
• Conduct model evaluation, experimentation, and performance optimization.
• Collaborate with domain experts, architects, and engineering teams to deliver production-ready solutions.
• Present technical findings and solution recommendations to stakeholders.

Must-Have Skills (Mandatory) Graph Neural Networks (Non-Negotiable)

• Proven hands-on experience implementing:
• Graph Convolution Networks (GCN)
• Graph Attention Networks (GAT)
• GraphSAGE
• Heterogeneous Graph Networks
• Temporal GNNs
• Experience solving real-world Graph ML problems.

Demonstrated Graph ML Delivery Experience

• Candidate must provide examples of prior graph-based machine learning implementations, including:
• Problem statement
• Graph modeling approach
• Architecture used
• Business outcome achieved

Note :

• Prior experience in power systems is not mandatory. However, prior Graph ML/GNN implementation experience is mandatory.

Python & Advanced Machine Learning Strong experience with:

• Python
• NumPy
• Pandas
• Scikit-learn
• Data processing and feature engineering

GNN Frameworks Hands-on expertise with:

• PyTorch Geometric (PyG)
• Deep Graph Library (DGL)
• TensorFlow GNN

Deep Learning Experience with:

• PyTorch
• TensorFlow
• Neural network design
• Hyperparameter tuning
• Model optimization

Graph Data Modeling Experience working with:

• Node and edge feature engineering
• Graph embeddings
• Knowledge graphs
• Graph representation learning

Communication & Stakeholder Management

• Ability to explain complex graph-based concepts to business stakeholders.
• Experience working in cross-functional delivery teams.

Job DescriptionAbout Client: The client specializes in delivering technology solutions and services to help businesses with digital transformation, software development, and IT consulting. It provides custom software development services across various platforms and technologies, catering to different industries and domains. The client helps businesses modernize their IT systems, adopt new technologies, and transform their operations to stay competitive in the digital age. Client is known for its emphasis on innovation, agility, and a collaborative work culture. The company encourages its employees to explore creative solutions and stay updated with the latest technology trends.

Rate Range: $50-$55/Hr

ApTask is a leading global provider of workforce solutions and talent acquisition services, dedicated to shaping the future of work. As an African American-owned and Veteran-owned company, ApTask offers a comprehensive suite of services, including staffing and recruitment solutions, managed services, IT consulting, and project management. With a focus on excellence, collaboration, and innovation, ApTask provides unparalleled opportunities for professional growth and development. As a member of the ApTask team, you will have the chance to connect businesses with top-tier professionals, optimize workforce performance, and drive success across diverse industries. Join us at ApTask and be part of our mission to empower organizations to thrive while fostering a diverse and inclusive work environment.

Applicants may be required to attend interviews in person or by video conference. In addition, candidates may be required to present their current state or government issued ID during each interview.

Candidate Data Collection Disclaimer: At ApTask, we prioritize safeguarding your privacy. As part of our recruitment process, certain Personally Identifiable Information (PII) may be requested by our clients for verification and application purposes. Rest assured, we strictly adhere to confidentiality standards and comply with all relevant data protection laws. Please note that we only collect the necessary information as specified by each client and do not request sensitive details during the initial stages of recruitment.