What are the responsibilities and job description for the Atmospheric Science Lead (Weather AI) position at Predictive Sales AI a Spectrum Communications & Consulting LLC Brand?
Job Title: Atmospheric Science Lead (Weather AI)
Location: Chicago, IL-Remote/Hybrid
About Us
At Predictive Sales AI (PSAI), we’re redefining how technology and intelligence transform digital marketing. Our AI-powered software enables home services businesses to make smarter, faster decisions—fueling growth through automation, prediction, and precision.
We’re seeking a a PhD-level meteorology/climatology expert to lead the scientific integrity and real-world performance of our weather feature—a core part of how we help home improvement businesses forecast demand, staff crews, optimize inventory, and plan outreach.
You’ll shape how weather and climate signals become trustworthy, explainable product outputs (not just “a model score”), working shoulder-to-shoulder with ML, Product, Data Engineering, and Customer teams.
Job Overview
As a PhD-level meteorology/climatology expert, you’ll translate atmospheric science into product-ready requirements, validate model behavior, define weather-impact signals relevant to commercial outcomes, and help the team ship credible, explainable weather intelligence at scale.
This role blends domain expertise applied analytics product collaboration. You’ll partner closely with data science, ML engineering, and product to ensure the PSAI weather feature is scientifically sound, robust across regions/seasons, and useful to non-technical users.
Key Responsibilities
We are looking for an individual who is organized, proactive, and detail-oriented. In this role, you will work closely with teams across the company. Here’s what we’re looking for:
Location: Chicago, IL-Remote/Hybrid
About Us
At Predictive Sales AI (PSAI), we’re redefining how technology and intelligence transform digital marketing. Our AI-powered software enables home services businesses to make smarter, faster decisions—fueling growth through automation, prediction, and precision.
We’re seeking a a PhD-level meteorology/climatology expert to lead the scientific integrity and real-world performance of our weather feature—a core part of how we help home improvement businesses forecast demand, staff crews, optimize inventory, and plan outreach.
You’ll shape how weather and climate signals become trustworthy, explainable product outputs (not just “a model score”), working shoulder-to-shoulder with ML, Product, Data Engineering, and Customer teams.
Job Overview
As a PhD-level meteorology/climatology expert, you’ll translate atmospheric science into product-ready requirements, validate model behavior, define weather-impact signals relevant to commercial outcomes, and help the team ship credible, explainable weather intelligence at scale.
This role blends domain expertise applied analytics product collaboration. You’ll partner closely with data science, ML engineering, and product to ensure the PSAI weather feature is scientifically sound, robust across regions/seasons, and useful to non-technical users.
Key Responsibilities
- Define the weather variables and derived indices most predictive for home improvement demand, such as:
- Heating/Cooling Degree Days, freeze/thaw cycles, precipitation intensity/duration
- Wind impacts, humidity/heat indices, storm severity proxies
- Event flags (hail, heavy rain, snow/ice), anomalies vs. normals, multi-day lead/lag effects
- Translate science into product requirements: how signals should behave, update, and explain themselves.
- Recommend and evaluate data sources (observations, forecasts, reanalysis) and define when to use each.
- Set policies for spatial/temporal resolution, downscaling/aggregation, and handling missing or biased coverage.
- Define uncertainty representation (probabilistic outputs, confidence, ensemble approaches) and guardrails against over-precision.
- Build the testing framework for:
- Regional/seasonal performance across climate zones
- Extreme events and edge cases (rapid temperature swings, heavy precipitation, hurricanes, winter storms)
- Drift and ongoing monitoring (forecast bias shifts, station density artifacts, vendor changes)
- Lead root-cause analysis when outputs look “off” and drive fixes with engineering.
- Create “plain English” explanations for non-technical users: why weather affected demand/forecast.
- Contribute to customer-facing methodology notes, FAQs, and sales enablement materials.
- Partner with Customer Success on high-stakes accounts where defensibility matters.
We are looking for an individual who is organized, proactive, and detail-oriented. In this role, you will work closely with teams across the company. Here’s what we’re looking for:
- Deep expertise in weather variability and extremes, forecast interpretation, and/or verification.
- Ability to work cross-functionally and turn scientific judgment into buildable specs, tests, and acceptance criteria.
- Strong communication skills: can explain uncertainty and limitations without killing usability.
- PhD in Meteorology, Atmospheric Science, Climatology, Earth System Science, or closely related field.
- Experience operationalizing weather data in products (weather APIs, forecast systems, risk/intelligence products).
- Familiarity with geospatial and atmospheric data workflows (e.g., gridded datasets, stations, NetCDF/GRIB concepts).
- Applied work linking weather to human/market outcomes (construction, home services, logistics, energy, insurance, etc.).
- Comfort collaborating with ML teams on feature engineering, causal pitfalls, and confounding factors.
- Innovative Environment: Be part of a forward-thinking company that values creativity and encourages the exploration of new ideas.
- Professional Growth: Access opportunities for continuous learning and career advancement within a supportive and dynamic team.
- Comprehensive Benefits: Enjoy a competitive salary, performance-based bonuses, flexible work arrangements, and a robust benefits package.
- Collaborative Culture: Work in a team-oriented environment where collaboration and mutual respect drive our success.