Senior Data Scientist & ML Engineer — Remote Production ML

Neo.Tax; United States; Remote; USD 190,000 - 210,000; Full time

Benefits offered by this job

Stock options

Health care plans

Wellness subsidy

401k

Paid time off

Family leave

Work from home

Job summary

Neo.Tax is automating R&D tax credits and software capitalization workflows by ingesting data from diverse systems and applying ML/LLMs to deliver in hours what used to take months.

The Senior Data Scientist + Machine Learning Engineer role is hands-on and product-oriented, turning ambiguous problems into measurable objectives and shipping robust ML solutions in collaboration with engineering and product teams.

Qualifications

• MS/PhD in Computer Science, Statistics, Mathematics, or a related quantitative field, or equivalent practical experience.
• 6+ years of industry experience shipping ML to production.
• Strong proficiency in Python and the modern data/ML ecosystem (NumPy/Pandas, scikit-learn, PyTorch or TensorFlow).
• Strong understanding of statistical modeling, experimentation, and evaluation (metrics, confidence intervals, A/B testing, bias/variance, error analysis).
• Experience building data pipelines and working with SQL and relational databases.
• Experience deploying and maintaining models in production (batch or real-time), including monitoring and iteration; comfortable owning operational concerns (reliability, latency, cost).
• Ability to operate with high ownership in ambiguous environments; strong communication and collaboration skills.
• Ability to effectively design and implement solutions without the help of AI.
• Experience with LLM evaluation, synthetic data generation, RAG, or tool-augmented agents.

Responsibilities

• Own ML/AI problem spaces end-to-end: Define success metrics, baseline, iterate, and push to production.
• Model development: Build and improve models across classification, information extraction, clustering, ranking, anomaly detection, and forecasting.
• LLM systems: Design prompt + retrieval + tool-calling pipelines; improve via labeling and evaluation.
• Data foundations: Define datasets, labeling strategies, and data quality checks; build generalizable features.
• Experimentation and evaluation: Design offline evaluations and online experiments; build dashboards to monitor regressions.
• Production ML engineering: Build/operate training/inference pipelines, model serving, data pipelines, and monitoring for quality and cost.
• Partner with engineering: Collaborate on productionization, reliability, latency, and cost; contribute to model-serving or batch pipelines.
• Cross-functional collaboration: Work with product, engineering, and customer teams to translate workflows into ML deliverables.
• Technical communication: Write specs and postmortems, document trade-offs, and communicate progress.

Skills

Python

ML Engineering

Data Science

Statistical Modeling

Experimentation

Data Pipelines

SQL

Production ML

Communication

Ambiguity Handling

Education

MS/PhD in CS/Stats/Math

Equivalent practical experience

Tools

PyTorch

TensorFlow

scikit-learn

Job description

Neo.Tax is automating R&D tax credits and software capitalization workflows by ingesting data from diverse systems and applying ML/LLMs to deliver in hours what used to take months.

The Senior Data Scientist + Machine Learning Engineer role is hands-on and product-oriented, turning ambiguous problems into measurable objectives and shipping robust ML solutions in collaboration with engineering and product teams.