Senior Data Scientist
@ EntrataSenior Data Scientist
This job is still taking applications, but it's been up a while.
About the job
Entrata, a global leader in AI-driven property management software since 2003, offers stability and innovation. As a Senior Data Scientist, you will lead data initiatives, collaborate across teams, and shape AI-powered solutions that redefine the industry.
Requirements
- Expertise in NLP/NLU/NLG models
- Proficiency in AI/ML pipelines
- Strong statistical analysis skills
- Experience with cloud ML services
- Project management experience
Qualifications
- BS/BA in related field
- 5+ years data science experience
- Proficiency in Python and SQL
- Knowledge of AI ethics and data governance
- Experience with Docker, Kubernetes
Full job description
We are seeking a Senior Data Scientist to help improve the quality and performance of Entrata’s AI models and applications. This role will focus on fine-tuning strategy, training data, experimentation, evaluation, and identifying the approaches that produce the best outcomes for complex property management workflows.
Responsibilities:
- Fine-tune and evaluate foundation models for Entrata-specific use cases using supervised fine-tuning and other post-training methods.
- Design and curate high-quality training datasets, including instruction data, preference data, and synthetic data.
- Develop evaluation frameworks and benchmarks to measure model accuracy, reasoning, reliability, and task performance.
- Conduct experiments to determine which models, datasets, prompts, and training approaches perform best for specific use cases.
- Perform model error analysis and identify opportunities to improve model behavior and output quality.
- Partner with machine learning engineers to move successful experiments into production.
- Develop approaches for measuring and improving model safety, consistency, and enterprise readiness.
- Translate business and product problems into measurable machine learning objectives.
Minimum Qualifications:
- 5+ years of experience in data science, machine learning, applied AI, or a related field.
- Hands-on experience working with large language models, including fine-tuning, evaluation, or model adaptation.
- Strong proficiency in Python and common machine learning frameworks.
- Experience designing experiments, analyzing model performance, and working with large datasets.
- Strong understanding of supervised learning, model evaluation, and statistical analysis.
- Experience building or evaluating machine learning systems in production environments.
- Ability to communicate technical findings clearly to engineering, product, and business stakeholders.
Preferred Qualifications:
- Experience with supervised fine-tuning, preference optimization, or other LLM post-training techniques.
- Experience creating synthetic training data or model-generated datasets.
- Experience building LLM evaluation frameworks, benchmark suites, or automated quality measurement systems.
- Familiarity with agentic AI systems, tool use, and retrieval-based applications.
- Experience working with enterprise, financial, legal, operational, or other domain-specific AI applications.
- Master’s degree in Computer Science, Machine Learning, Statistics, Mathematics, or a related quantitative field, or equivalent practical experience.
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