[Remote] Data Scientist - Senior

Note: The job is a remote job and is open to candidates in USA. The hiring company is confidential. The Senior Data Scientist will develop and operationalize AI-powered solutions for veterinary health care, including clinical decision support, disease risk modeling, and automated interpretation of diagnostic reports. The role applies machine learning, NLP, and generative AI to clinical data and partners with veterinary experts and data engineers to build scalable, explainable workflows.

Responsibilities

• Design, prototype, and operationalize AI models using Python, Databricks, and MLflow for veterinary healthcare applications
• Apply machine learning and natural language processing (NLP) to structured and unstructured clinical data, including EMR records, diagnostic imaging, and laboratory/pathology results
• Develop predictive models for disease risk stratification, prognosis, and treatment outcome prediction
• Collaborate with veterinary subject matter experts to translate domain questions into reproducible data science workflows
• Develop explainable AI models to support clinical decision-making and trust in automated recommendations
• Contribute to the creation of quality evaluation frameworks for AI-driven tools
• Partner with data engineers to implement scalable data ingestion and processing systems on Databricks
• Utilize Claude Code for AI coding assistance
• Apply prompt engineering guidelines, strategies, and optimization techniques to improve generative model outputs
• Apply retrieval-augmented generation (RAG) and related techniques—such as context engineering, embedding-based search, and hybrid knowledge reasoning
• Participate in agile development cycles, maintaining thorough technical documentation and experiment traceability
• Use best practices for version control using Git

Skills

• Strong collaboration, communication, and documentation skills
• Proven experience working with large, distributed datasets
• Experience with data exploration, statistical analyses, and visualizations
• Strong statistical foundation with broad knowledge of deterministic and probabilistic statistical methods
• Strong background in supervised/unsupervised machine learning, or natural language processing (NLP)
• Experience with advanced Named Entity Recognition (NER) techniques to extract structured entities from text data
• Demonstrated mastery of prompt engineering methods—prompt engineering, fine-tuning, self-reflection, chain-of-thought reasoning, and declarative prompting
• Experience with Databricks platform
• Strong software development skills
• Experience using Git for version control in a collaborative team environment, including branching, pull requests, and code review
• Bachelor's in Data Science, Computer Science, Biomedical Engineering, or a related quantitative field
• 5+ years of experience developing ML/AI solutions in Python (Pandas, PySpark, scikit-learn, MLflow)
• Technically Experienced
• Designs and builds new AI models utilizing off-the-shelf machine learning algorithms and tools
• Works efficiently and independently along the whole data science pipeline – acquisition, exploration, cleaning, modeling and evaluation
• Experience with various data structures and common methods in data transformation
• Ability to create new tools and packages for data science use in statistical/data science programming environments such as Python/Pandas/PySpark
• Ability to create new complex SQL data queries
• Focused Experience with doing data sourcing, manipulation, analysis and modeling
• Think Big – demonstrates strategic mindset and cultivates innovation
• Ensures Impact – talented at planning and driving results
• Works Across Organization – Skilled capabilities in building informal and formal networks, with strong persuasion skills
• Brings People with you – Capable of developing talent to meet both their career and organizational goals
• Some experience with Machine learning (supervised and unsupervised) modeling
• Experience with using Claude Code for coding assistance
• Hands-on experience developing and orchestrating AI agents or agentic workflows using LLM frameworks
• Classification – decision trees, logistic regression, random forest, SVM, neural networks
• Familiarity with healthcare or life sciences datasets — electronic medical records (EMR), radiology, pathology, or epidemiological data preferred
• Knowledge of veterinary health informatics, disease taxonomy, or ontology-based data integration
• Experience with knowledge graph, semantic web or ontology development techniques

Benefits

• Remote (within U.S.)

Company Overview

Company H1B Sponsorship