[Remote] Data Scientist

Note: The job is a remote job and is open to candidates in USA. SoTalent is seeking a Senior Data Scientist / AI Engineer to apply machine learning, NLP, LLMs, and Generative AI to scientific discovery and knowledge creation. The role involves designing, developing, deploying, and optimizing production-ready AI systems that transform scientific content and datasets into intelligent products, research insights, decision support, and content understanding.

Responsibilities

• Design and develop machine learning, NLP, and Generative AI solutions
• Build intelligent systems that support:
• Scientific Discovery
• Knowledge Extraction
• Decision Support
• Research Insights
• Content Understanding
• Translate ambiguous research and business challenges into measurable AI solutions
• Develop scalable and production-ready AI applications
• Build solutions that extract value and insights from diverse knowledge sources
• Select and implement the most effective approach for each problem
• Transform unstructured text into actionable intelligence
• Build applications using frontier AI models
• Develop and optimize solutions utilizing:
• OpenAI GPT Models
• Anthropic Claude
• Google Gemini
• Small Language Models (SLMs)
• Prompt Engineering
• Fine-Tuning
• Model Evaluation
• Retrieval-Augmented Generation (RAG)
• Context Enrichment
• Guardrails & Reliability Controls
• AI Workflow Orchestration
• Ensure high-quality, trustworthy AI outputs
• Develop intelligent systems supporting:
• Semantic Search
• Vector Search
• Information Retrieval
• Content Discovery
• Relevance Ranking
• Scientific Search Optimization
• Citation Analysis
• Improve the ability of researchers to find relevant knowledge quickly and accurately
• Develop recommendation engines for scientific content
• Build personalization and ranking models
• Improve relevance and user engagement
• Support intelligent content discovery experiences
• Optimize research workflows and knowledge access
• Build, deploy, and maintain production-ready machine learning systems
• Create robust AI services and workflows
• Implement scalable inference pipelines
• Ensure performance, reliability, and maintainability
• Support enterprise-grade AI operations
• Develop reusable Python packages and components
• Create scalable data pipelines for:
• Data Preparation
• Feature Engineering
• Training
• Inference
• Monitoring
• Experimentation
• Apply software engineering best practices throughout development
• Design model evaluation methodologies
• Measure:
• Accuracy
• Relevance
• Precision
• Recall
• Business Impact
• User Value
• Continuously refine and improve model performance
• Compare alternative modeling approaches
• Drive quality improvements through experimentation
• Support the complete machine learning lifecycle:
• Model Deployment
• Monitoring
• Drift Detection
• Automated Retraining
• Performance Tracking
• Model Governance
• Continuous Improvement
• Ensure AI solutions remain effective in production environments
• Work closely with:
• Software Engineers
• Product Managers
• UX Teams
• Research Scientists
• Data Analysts
• Domain Experts
• Business Stakeholders
• Translate technical capabilities into meaningful business and research outcomes
• Explain complex AI concepts to technical and non-technical audiences
• Present:
• Insights
• Trade-Off Analyses
• Recommendations
• Model Behavior
• Performance Findings
• Support informed decision-making across the organization

Skills

• Strong background in:
• • Data Science
• • Machine Learning
• • Artificial Intelligence
• • Natural Language Processing
• • Statistics
• • Applied Mathematics
• • Computer Science
• • Related Quantitative Disciplines
• • Experience developing machine learning solutions
• • Strong knowledge of:
• • Supervised Learning
• • Unsupervised Learning
• • Model Evaluation
• • Feature Engineering
• • Statistical Analysis
• • Experience building NLP and language understanding solutions
• • Experience working with large-scale textual datasets
• • Knowledge of semantic search and information retrieval techniques
• Hands-on experience with:
• • OpenAI GPT Models
• • Anthropic Claude
• • Google Gemini
• • Fine-Tuning LLMs
• • Prompt Engineering
• • Retrieval-Augmented Generation (RAG)
• • Python
• • Production Software Development
• • Testing & Code Quality
• • Reusable Package Development
• • Pandas
• • NumPy
• • SciPy
• • Scikit-learn
• • Matplotlib
• • PyTorch
• • TensorFlow
• • Large Language Models (LLMs)
• • Embeddings
• • NLP Pipelines
• • Semantic Search
• • Question Answering
• • Summarization
• • Knowledge Extraction
• • Knowledge Graphs
• • Ontologies
• • Scientific Content Mining
• • Recommendation Systems
• • Ranking Algorithms
• • Evidence-Grounded Generation
• • Conversational AI
• • Model Monitoring
• • Drift Detection
• • Automated Retraining
• • Production Inference Pipelines
• • AI System Reliability
• • Analytical Thinking
• • Scientific Curiosity
• • Problem Solving
• • Experimentation Mindset
• • Communication Skills
• • Stakeholder Collaboration
• • Product Thinking
• • Attention to Quality
• • Continuous Learning

Benefits

• Remote, US
• Hybrid work setting

Company Overview