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Probabilistic Modeling Jobs in Wallingford, CT (NOW HIRING)

R&D Analyst/Engineer

Windsor, CT · On-site

$135K - $180K/yr

Develop and implement innovative modeling techniques to represent emerging supply- and demand-side resources (renewables, storage, DERs, demand response, electrification) in probabilistic reliability ...

Genetics Tutor

Hartford, CT · Remote

$18 - $40/hr

Ability to explain linkage analysis, Hardy-Weinberg equilibrium, and gene regulation models while ... Emphasizes probabilistic reasoning and connects genetics to genetic counseling, forensic science ...

Genetics Tutor

New Haven, CT · Remote

$18 - $40/hr

Ability to explain linkage analysis, Hardy-Weinberg equilibrium, and gene regulation models while ... Emphasizes probabilistic reasoning and connects genetics to genetic counseling, forensic science ...

Experience validating AI/ML-enabled systems, distinguishing deterministic and probabilistic tool ... Experience with AI governance processes, including AI use case tracking, model risk classification ...

Experience validating AI/ML-enabled systems, distinguishing deterministic and probabilistic tool ... Experience with AI governance processes, including AI use case tracking, model risk classification ...

Experience validating AI/ML-enabled systems, distinguishing deterministic and probabilistic tool ... Experience with AI governance processes, including AI use case tracking, model risk classification ...

Data Scientist

Windsor, CT · On-site

$117K - $146K/yr

Responsible for analytics and predictive modeling of the region's electricity demand across all ... Experience working with big data, geospatial analytics, and/or probabilistic forecasting

Probabilistic Modeling information

What is the difference between Probabilistic Modeling vs Data Scientist?

AspectProbabilistic ModelingData Scientist
Required CredentialsDegree in statistics, mathematics, or related fields; knowledge of probability theoryDegree in computer science, statistics, or related fields; programming skills
Work EnvironmentResearch-focused, often in analytics or data science teamsCross-functional teams, including business, engineering, and analytics
Industry UsageUsed in analytics, finance, healthcare, and research for modeling uncertaintyApplied across industries for data analysis, predictive modeling, and decision-making

Probabilistic Modeling focuses on developing models based on probability theory to understand uncertainty, while Data Scientists utilize a broader set of skills including programming, data analysis, and machine learning to extract insights from data. Both roles often overlap but serve different primary purposes within data-driven organizations.

What is probabilistic modeling?

Probabilistic modeling is a mathematical framework used to represent uncertain events or data by using probability distributions. Instead of giving a single outcome, it accounts for variability and randomness, allowing predictions and inferences even when information is incomplete or ambiguous. Probabilistic models are widely used in fields like statistics, machine learning, finance, and engineering to analyze data, make forecasts, and support decision-making under uncertainty.

What are the key skills and qualifications needed to thrive as a probabilistic modeler, and why are they important?

To thrive as a Probabilistic Modeler, you need a strong background in mathematics, statistics, and probability theory, often supported by a degree in applied mathematics, statistics, or a related field. Proficiency with programming languages like Python or R, and experience with statistical modeling tools and software such as TensorFlow or PyMC, are typically required. Strong analytical thinking, problem-solving abilities, and effective communication skills help translate complex models into actionable insights. These skills are vital for designing accurate models, interpreting uncertainty, and supporting data-driven decisions across various industries.

What are some common challenges faced by professionals in probabilistic modeling roles, and how can they be managed?

Professionals in probabilistic modeling often encounter challenges such as working with incomplete or noisy data, choosing the right model complexity, and ensuring model interpretability for stakeholders. Managing these challenges involves strong statistical knowledge, regular collaboration with domain experts, and effective communication to translate complex results for non-technical team members. Staying up-to-date with the latest tools and methodologies, and participating in peer reviews, can also help maintain model accuracy and reliability.

Senior Electric Grid Planning Analyst

ISO New England, Inc.

Windsor, CT • On-site

$105K - $135K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 9 days ago


Job description

ISO New England is the independent system operator responsible for ensuring the safe and reliable flow of electricity in our region and planning for the future of the electric grid. We are at the forefront of New England's ongoing transition to clean energy.
ISO New England is at the forefront of the transformation to a clean energy grid in the Northeast. As advanced technologies integrate into the power grid, the electricity demand and generation mix of the power system will experience a major shift and require innovative solutions to create a reliable and efficient grid. The Capacity Requirement and Accreditation group within System Planning seeks an innovative engineer or Analyst to meet these exciting challenges.
NOTE: This role is currently located in Windsor, CT until it permanently moves to Holyoke, MA, which is currently expected to occur in 2028.
What we offer you:
  • Hybrid work environment - 3 days/week onsite
  • Distance-based relocation assistance available
  • Competitive compensation with a base salary + performance bonus
  • Robust benefits package, including:
    • Enhanced 401(k) and financial planning support
    • Tuition reimbursement and professional development
    • Wellness programs, including an onsite gym
    • Onsite luncheon spaces with free coffee and a variety of dining options
    • Flexible work hours
    • Employee Business Networks
  • A stable, mission-driven workplace where your impact truly matters

How you will make an Impact
The individual will support regional and national resource capacity planning and accreditation initiatives of capacity auction reforms by contributing technical analyses, study development, and stakeholder engagement activities. This role supports the implementation and refinement of methodologies used to assess resource contributions to system adequacy and reliability and represents the organization in regional and national forums by providing analytical support for studies, committees, and regulatory discussions.
  • Perform bulk power system simulations using industry standard software tools, including but not limited to GE MARS, SERVM, and PLEXOS
  • Provide technical and procedural leadership by coordinating and facilitating work within the ISO and across a wide range of stakeholders, including Market Participants, NEPOOL and ISO committees, and regional and national regulatory entities
  • Collaborate with ISO staff and external consultants to conduct resource adequacy and reliability studies, and prepare clear, comprehensive written reports documenting objectives, assumptions, methodologies, results, and recommendations
  • Support and actively participate in internal and external regional and national committees, task forces, and working groups, as required
  • Respond to data and information requests from regional and national reliability organizations, as well as state and federal regulators
  • Effectively communicate complex analyses to diverse stakeholder audiences

What we are looking for
  • Bachelor's degree in engineering, science, statistics, or a related field, with a minimum of 5-10 years of progressively responsible experience in resource adequacy and reliability studies
  • Demonstrated ability to work independently, bringing a high degree of judgment, patience, and attention to detail, while collaborating effectively across teams and communicating complex technical concepts clearly in both written and verbal formats
  • Knowledge of the New England generation and transmission system, including planning practices, real time operational considerations, and system topology

Desired not required:
  • Graduate degree in engineering, science, statistics, or a related field
  • Demonstrated expertise in probabilistic resource adequacy metrics (e.g., LOLE, EEU) and/or economic production cost modeling, including the ability to guide methodological discussions and assumptions
  • Proven experience working within the ISONE/NEPOOL framework, with the ability to effectively engage in committee and stakeholder forums
  • Familiarity with NPCC, NERC, ISONE, and/or FERC reliability and regulatory requirements
  • Prior hands-on experience applying probabilistic modeling tools in resource adequacy or reliability analyses
  • Strong analytical and problem-solving skills, with working knowledge of at least one programming language (e.g., Python, R, MATLAB, or SAS);

This employer will not sponsor applicants for work visas for this position (ex: H-1B, F-1/CPT/OPT, O-1, E-3, TN, J, etc.).
The expected salary range for this position is $105,000 - $135,000 per year. This role is also eligible for an annual performance bonus, comprehensive health insurance (medical, dental and vision), flexible spending and health savings accounts, a 401(k) plan with generous employer contributions and a student debt benefit, life and AD&D insurance, disability insurance, critical illness and hospital indemnity benefits, paid time off, paid leave, a wellness program, an employee assistance program and other great company perks.
#LI-HYBRID
This is a U.S. based role. If the successful candidate resides outside of the U.S., relocation will be required.
Equal Opportunity: We are proud to be an EEO employer. Applicants for employment are considered without regard to race, color, religion, creed, sex (including pregnancy, childbirth, and related medical conditions), gender identity or expression, sexual orientation, citizenship, national origin, age, ancestry, marital status, disability (including learning, mental, intellectual, and physical), service in the uniformed services, genetic information, or any other status protected by applicable law.
Drug Free Environment: We maintain a drug-free workplace and perform pre-employment substance abuse testing.