Staff Data Scientist
Staff Data Scientist building agentic AI and optimization solutions to improve care operations and marketplace matching at Honor (Home Instead). Requires 7+ years experience, strong ML foundations, and deep expertise in either Agentic AI systems or optimization algorithms.
About the job
About the work
- Leverage data to solve a wide variety of meaningful business problems using the appropriate level of technical complexity.
- Partner closely with Engineering, PM, and Care Operations to collaboratively define strategy and execute against it.
- Design and implement robust frameworks and metrics to measure whether data products are functioning as expected and driving business impact.
- Research operational/logistical problems and proactively identify potential solutions.
- Lead the design, implementation, and evaluation of descriptive and predictive models.
- Champion the use of LLM-driven workflows across the company. Partner with Engineering to design architectures and build production-ready systems that leverage agents in our core product features as well as in tools that drive developer productivity.
About you
- 7+ years of professional experience solving complex business problems, and shipping/maintaining Python in a production environment.
- Strong foundation in traditional predictive machine learning (e.g., classification, regression, tree-based models like XGBoost) and know when to use standard models versus LLMs.
- Deep professional expertise in at least one of the following two areas:
- Optimization: Formulating and solving complex logistical/allocation problems (e.g., linear/integer programming) in a business setting.
- Agentic AI: Deep technical depth in building, orchestrating, and establishing best practices for agentic systems (e.g., utilizing LLMs for autonomous decision-making and tool-use). Concrete experience building agentic workflows that drive business impact.
- Set success metrics upfront and proactively investigate how your technical solutions influence overarching business goals.
- Excellent mathematical and statistical foundations, including a degree in a quantitative field (such as Computer Science, Mathematics, Statistics, Economics, Physics) or equivalent professional experience.
- Able to manage product ambiguity, seeking clarity when necessary, to ensure that we are solving the right problem and driving measurable outcomes.
- Rapidly iterate and deliver technical solutions that maximize business impact.
- Clear and persuasive communication skills, both written and verbal, with the ability to translate complex technical concepts for diverse, non-technical stakeholders.
- Accountable end-to-end for the entire project lifecycle. Proactively anticipate and drive resolution for potential issues across dependencies.
Bonus points if you have professional experience with
- Designing experiments and applying causal inference methods to rigorously determine business impact.
- Developing systems to optimize portfolio allocation in a two-sided marketplace (e.g., ideal matches of people needing and providing care, hiring needs, demand forecasting).
- Modern MLOps practices, cloud platforms (AWS), containerization (Docker), or CI/CD pipelines.
- Working with sensitive data, including PII or PHI, within a strict, HIPAA-compliant environment.
Skills
Python, Machine Learning, Xgboost, LLMs, Agentic AI, Optimization Algorithms, Linear Programming, Integer Programming, Causal Inference, AWS, Docker, MLOps, CI/CD
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