Data Scientist/ AI Engineer

Compunnel

$110K — $130K *
Healthcare
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree in Data Science, Computer Science, Biomedical Engineering, or a related field.
  • 5+ years of experience in developing ML/AI solutions using Python.
  • Strong statistical background with knowledge of deterministic and probabilistic methods.
  • Proficient in supervised/unsupervised machine learning and natural language processing.
  • Experience with advanced Named Entity Recognition (NER) techniques for data extraction.
  • Demonstrated mastery of prompt engineering methods and techniques.
  • Familiarity with the Databricks platform.

Responsibilities

  • Design and operationalize AI models for veterinary healthcare using Python and Databricks.
  • Apply machine learning and NLP to both structured and unstructured clinical data.
  • Develop predictive models for disease risk and treatment outcomes.
  • Collaborate with veterinary experts to create reproducible data science workflows.
  • Develop explainable AI models to enhance clinical decision-making trust.
  • Create quality evaluation frameworks for AI tools.
  • Partner with data engineers to build scalable data ingestion systems.

Benefits

  • Collaborative work with veterinary subject matter experts.
  • Engagement in cutting-edge AI projects that directly impact animal health.
  • Opportunity to utilize advanced AI tools and methodologies.
  • Dynamic and agile development environment for professional growth.
  • Access to continual learning and skill enhancement opportunities.
Full Job Description
Job Description Summary

We are seeking an experienced AI Engineer (Data Scientist) to develop AI-powered solutions that advance veterinary health care. Using Python, the Databricks platform and various generative AI tools, you will design models and analytical workflows that support clinical decision support systems, disease risk modeling, and automated interpretation of radiology and pathology reports. This role combines exceptional technical expertise with domain awareness in animal health and diagnostic data.

Job Description

Primary Duties and 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

Required Skills and Abilities

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.

Nice to Have Skills and Abilities

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

Leveling Guide

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.

Skilled Core Competencies (building on Data Scientist)

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.

Education

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).

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