Senior Data Scientist
SoTalentAbout the role
Senior Data Scientist
📍 Location: Philadelphia, Pennsylvania, United States
🏢 Industry: Information Services
💼 Work Setting: Onsite
Are you passionate about leveraging advanced AI and data science techniques to accelerate discovery, unlock insights from complex data, and build next-generation intelligent applications? We are seeking a Senior Data Scientist to design, develop, and scale innovative AI solutions that drive knowledge exploration, research enablement, and advanced analytics. This role offers the opportunity to work with cutting-edge technologies including machine learning, natural language processing, knowledge graphs, retrieval systems, and generative AI to solve complex challenges and create impactful solutions.
Key Responsibilities
Design, develop, and deploy advanced AI and machine learning solutions to support knowledge discovery and decision-making.
Build and optimize Retrieval-Augmented Generation (RAG) systems and Large Language Model (LLM)-powered applications for complex information retrieval and reasoning tasks.
Develop intelligent solutions that leverage structured and unstructured data to generate actionable insights.
Design and integrate knowledge graphs to enhance data connectivity, contextual understanding, and information discovery.
Collaborate with cross-functional teams to define requirements, identify opportunities, and deliver scalable AI-driven solutions.
Develop, evaluate, and optimize machine learning and deep learning models for production environments.
Apply Natural Language Processing (NLP) techniques to extract, analyze, classify, and generate insights from large-scale text datasets.
Establish model evaluation frameworks and performance metrics to ensure accuracy, reliability, and business impact.
Work with large and complex datasets, ensuring efficient data processing, integration, and governance.
Stay current with emerging AI technologies and incorporate innovative approaches into product and research initiatives.
Contribute to AI architecture decisions, best practices, and technical strategy.
Required Qualifications
Bachelor's, Master's, or PhD in Data Science, Computer Science, Artificial Intelligence, Statistics, Mathematics, Engineering, or a related quantitative field.
Significant hands-on experience in Data Science, Machine Learning, and Artificial Intelligence roles.
Strong expertise in Natural Language Processing (NLP), machine learning, and generative AI applications.
Proven experience building and deploying production-grade software solutions using Python.
Experience developing and implementing Retrieval-Augmented Generation (RAG) systems and Large Language Model (LLM) applications.
Strong understanding of statistical analysis, predictive modeling, and experimental methodologies.
Experience working with large-scale structured and unstructured datasets.
Proficiency with modern AI, machine learning, and deep learning frameworks.
Strong analytical, problem-solving, and software engineering skills.
Ability to work independently while collaborating effectively with diverse technical and business teams.
Preferred Qualifications
Experience designing and implementing knowledge graph solutions and semantic search systems.
Familiarity with cloud platforms, MLOps practices, and model deployment pipelines.
Experience optimizing AI systems for scalability, performance, and reliability.
Knowledge of vector databases, retrieval systems, and information discovery architectures.
Experience leading technical initiatives and mentoring junior data scientists.
Exposure to research-oriented environments and advanced analytical applications.
Key Skills
Data Science
Machine Learning
Generative AI
Large Language Models (LLMs)
Retrieval-Augmented Generation (RAG)
Natural Language Processing (NLP)
Knowledge Graphs
Deep Learning
Python Programming
Statistical Analysis
Model Evaluation & Optimization
Information Retrieval Systems
Data Engineering & Preparation
AI Solution Architecture
Predictive Analytics
Cross-Functional Collaboration
Research & Innovation
Production AI Deployment
Responsibilities
- Design, develop, and deploy advanced AI and machine learning solutions to support knowledge discovery and decision-making.
- Build and optimize Retrieval-Augmented Generation (RAG) systems and Large Language Model (LLM)-powered applications.
- Develop intelligent solutions leveraging structured and unstructured data to generate actionable insights.
- Design and integrate knowledge graphs to enhance data connectivity and information discovery.
- Collaborate with cross-functional teams to define requirements and deliver scalable AI-driven solutions.
- Develop, evaluate, and optimize machine learning and deep learning models for production environments.
- Apply Natural Language Processing (NLP) techniques to extract and analyze insights from large-scale text datasets.
- Establish model evaluation frameworks and performance metrics.
Qualifications
- Bachelor's, Master's, or PhD in Data Science, Computer Science, Artificial Intelligence, Statistics, Mathematics, Engineering, or a related quantitative field.
- Significant hands-on experience in Data Science, Machine Learning, and Artificial Intelligence roles.
- Strong expertise in Natural Language Processing (NLP), machine learning, and generative AI applications.
- Proven experience building and deploying production-grade software solutions using Python.
- Experience developing and implementing Retrieval-Augmented Generation (RAG) systems and LLM applications.
- Strong understanding of statistical analysis, predictive modeling, and experimental methodologies.
- Experience working with large-scale structured and unstructured datasets.
- Proficiency with modern AI, machine learning, and deep learning frameworks.
Skills mentioned
About SoTalent
A recruitment media and candidate acquisition agency helping employers and hiring partners connect with relevant talent at scale. We promote live job opportunities across social, professional and digital channels, then screen and evaluate candidates to discover relevant opportunities while supporting employers with quality applicant flow. Focused on high-volume hiring sectors including healthcare, logistics, technology, engineering and skilled professions.