Advanced Data Scientist at Honeywell
Raleigh, NC
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Jul 23, 2026
Raleigh, NC
Jul 25, 2026
What this job asks for AI summary
This role sits within a utilities analytics team and centers on building statistical and machine learning models for problems such as grid reliability, predictive maintenance, load forecasting, and anomaly detection. Day-to-day work spans the full ML lifecycle — feature engineering, model training, deployment, and monitoring — primarily on Databricks, using both classical statistical methods and modern ML approaches against telemetry and SCADA data. It suits a quantitatively trained practitioner with production modeling experience who can also communicate findings to non-technical audiences.
Mid level · 3+ years · Raleigh-Cary, NC · Bachelor's required · Full-time
“or” means any one of them counts — you don't need all of them.
Posted 2 times — it's one opening, so apply once.
We read this from the posting text with AI. Skim the description below before ruling yourself out.
How this req sits in the market our data
Roughly 15 people in the Raleigh-Cary, NC area plausibly meet what this posting asks for (data scientists). range 3–20
Applicant volume Moderate — A normal amount of company. The rare requirements below are what will separate a shortlisted application from the rest.
Rare in this occupation — lead with these, and say what you built with them.
Most people in this occupation already list these. Still required — just not what gets you shortlisted.
What the occupation pays Median $123,364 (middle half $87,094–$148,700).
Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Jul 28, 2026. It is a model, not a headcount.
Why we read it this way (8)
The title 'Advanced Data Scientist' carries no standard seniority level word, so the title states no level. The experience requirement is 3+ years (Bachelor's), 2+ years (Master's), or 1+ year (PhD), which maps to a Mid-level role on the career ladder.
Degree requirement: the JD states 'Bachelor's degree or equivalent' as a hard gate, but 'equivalent' experience is explicitly accepted, so the degree requirement is set to None per schema rules. However, the field of study (Statistics, Applied Mathematics, Physics, Engineering, Data Science) is a hard gate — only the specific degree level is waived by the equivalency clause.
The R packages (tidyverse, lme4, glmmTMB, glmnet, mgcv) and Python libraries (PySpark, pandas, NumPy, scikit-learn, statsmodels, XGBoost) are all listed together under the 'YOU MUST HAVE' requirements section and are treated as hard gates.
Databricks-specific sub-features (Feature Store, Experiment Track, Model Serving, Mosaic AI) are captured under the parent 'Databricks' skill, as they are sub-features of the same platform rather than separately marketed tools.
SCADA and GIS appear under the 'WE VALUE' (preferred) section alongside AMI and OMS data; all are marked preferred.
PyTorch and GeoPandas appear under 'WE VALUE' and are marked preferred.
LLMs appear under 'WE VALUE' as 'generative AI and LLM-based solutions as complementary tools' and are marked preferred.
No compensation figures are stated in the posting.
Read the full posting
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