ZipRecruiter

Log In

1

Seasonal Innovation Scientist Jobs (NOW HIRING)

Codvo.ai

Data Scientist (Dallas)

Texas, IL

We believe in a culture of innovation, collaboration, and growth, where engineers can experiment ... Extract and analyze the 30-day historian pull - identify operating modes, load patterns, seasonal ...

Garrett Popcorn Shops

Product Innovation Manager

Aurora, IL · On-site

$120K - $135K/yr

Own and manage innovation pipeline, including new products, seasonal offerings, limited time offers ... Degree in Food Science or Culinary Arts, Certified Culinary Scientist, Certified Research Chef, or ...

Propel Education

Innovation Instructor

Birmingham, AL

The program term will run on a seasonal basis (Fall, Spring, and Summer). At the conclusion of this ... science, code, creativity and using technology to support learning. 4. Problem-solver willing to ...

Wonderful Orchards

R&D Scientist (CCA)

Lost Hills, CA · On-site

... daily, seasonal, and yearly technical and research tasks at their base location and as needed ... Innovation-oriented, seeking to address current and future challenges with inquisitiveness and ...

Irca Group

R&D Scientist

Affton, MO

We offer every day and seasonal solutions to 3 macro channels: Gourmet, Food Manufacturing and ... paced innovation environment. This position is based onsite in Affton, Missouri, and requires ...

Irca Group

R&D Scientist

Affton, MO

We offer every day and seasonal solutions to 3 macro channels: Gourmet, Food Manufacturing and ... paced innovation environment. This position is based onsite in Affton, Missouri, and requires ...

Irca Group

R&D Scientist

Affton, MO · On-site

We offer every day and seasonal solutions to 3 macro channels: Gourmet, Food Manufacturing and ... paced innovation environment. This position is based onsite in Affton, Missouri, and requires ...

previous pagenext page

Showing results 21-40

All JobsInnovation Scientist JobsSeasonal Innovation Scientist Jobs

Seasonal Innovation Scientist information

What is the difference between Seasonal Innovation Scientist vs Product Development Specialist?

AspectSeasonal Innovation ScientistProduct Development Specialist
Required CredentialsBachelor's or Master's in Science, Innovation, or related fieldsBachelor's or Master's in Business, Engineering, or related fields
Work EnvironmentResearch labs, innovation centers, seasonal project teamsProduct teams, R&D departments, manufacturing settings
Employer & Industry UsageRetail, consumer goods, seasonal product companiesManufacturers, tech firms, consumer goods companies
Common Search & Comparison IntentUnderstanding roles in seasonal innovation projectsComparing roles in product development processes

The Seasonal Innovation Scientist focuses on developing innovative products tailored for specific seasons, often working in research and seasonal project teams. In contrast, a Product Development Specialist handles the entire product lifecycle, from concept to launch, across various product lines. Both roles require similar educational backgrounds but differ in their focus areas and work environments.

What cities are hiring for Seasonal Innovation Scientist jobs? Cities with the most Seasonal Innovation Scientist job openings:
What are the most commonly searched types of Innovation Scientist jobs? The most popular types of Innovation Scientist jobs are:
What states have the most Seasonal Innovation Scientist jobs? States with the most job openings for Seasonal Innovation Scientist jobs include:
Seasonal Innovation Scientist jobs near you

Data Scientist (Dallas)

Codvo.ai

Texas, IL

Full-time

Re-posted 10 days ago

Job description

Data Scientist 

 

About Us: 

At Codvo, we are committed to building scalable, future-ready data platforms that power business impact. We believe in a culture of innovation, collaboration, and growth, where engineers can experiment, learn, and thrive. Join us to be part of a team that solves complex data challenges with creativity and cutting-edge technology.


Role Summary 

The on-site technical presence during the pilot and Wave 1. Works directly with the customer's

maintenance team to validate alerts, tune models, and build trust in the platform's outputs.

This role requires someone who can explain machine learning predictions in maintenance

engineering language, not data science jargon.


Responsibilities 

Discovery & Baseline (Weeks 1-2)

  • Conduct the BMS protocol audit alongside the customer's controls engineer - identify available tags, data quality, polling rates, historian configuration
  • Extract and analyze the 30-day historian pull - identify operating modes, load patterns, seasonal variations, and data gaps
  • Build the baseline operating profile for each monitored equipment unit
  • Review the customer's maintenance logs - identify the 3-5 known fault events that will serve as ground truth validation
  • Map the customer's equipment taxonomy to NEIO's equipment family catalog - confirm coverage, flag gaps

Model Tuning & Validation (Weeks 3-5)

  • Monitor live anomaly scores and triage the first alerts - determine true positive vs. false positive vs. ambiguous
  • Facilitate the alert review sessions with the site maintenance lead - present alerts in context, gather feedback, document site-specific operating knowledge that affects interpretation
  • Tune the physics constraint gate to the site's operating ranges - adjust thermodynamic bounds, load-dependent thresholds, equipment-specific parameters
  • Calibrate fault classification confidence thresholds - Platt scaling, ECE measurement, reliability diagram review
  • Validate time-to-failure estimates against known maintenance history
  • Document all tuning decisions and rationale - this becomes the playbook for fleet rollout

Phase 2 (Wave 1 Sites)

  • Travel to Wave 1 sites for the 1-week discovery phase at each site
  • Conduct on-site tag mapping review with each site's controls engineer
  • Facilitate the alert review session at each Wave 1 site
  • Train the offshore Data Scientist on site-specific tuning decisions so they can handle
  • Wave 2 remotely

 

 

Expected Background 

  • 5+ years in applied data science or machine learning - predictive maintenance, anomaly detection, or industrial process optimization
  • Strong understanding of time-series analysis, classification models (XGBoost, LightGBM), and calibration techniques
  • Ability to explain model behavior to non-technical maintenance engineers - "the model flagged this because superheat is trending 3 degrees above normal for this load condition" not "the feature importance vector shows..."
  • Comfortable working on-site at a data center or industrial facility
  • Experience with HVAC, mechanical, or electrical systems is a strong advantage - someone who knows what a chiller does, what COP means, why approach temperature matters
Employment Type: FULL_TIME

Apply