Expert understanding of modeling techniques such as Bayesian modeling, Classification models, Cluster analysis, Neural Network, Non-parametric methods, and Multivariate statistics * Experience ...
Expert understanding of modeling techniques such as Bayesian modeling, Classification models, Cluster analysis, Neural Network, Non-parametric methods, and Multivariate statistics * Experience ...
Expert understanding of modeling techniques such as Bayesian modeling, Classification models, Cluster analysis, Neural Network, Non-parametric methods, and Multivariate statistics * Experience ...
Expert understanding of modeling techniques such as Bayesian modeling, Classification models, Cluster analysis, Neural Network, Non-parametric methods, and Multivariate statistics * Experience ...
Blend multiple alpha forecasts into meta-models and portfolio signals, leveraging ensemble and Bayesian methods. * Develop portfolio construction and optimization techniques and analysis tools to be ...
Quick apply
Blend multiple alpha forecasts into meta-models and portfolio signals, leveraging ensemble and Bayesian methods. * Develop portfolio construction and optimization techniques and analysis tools to be ...
Blend multiple alpha forecasts into meta-models and portfolio signals, leveraging ensemble and Bayesian methods. * Develop portfolio construction and optimization techniques and analysis tools to be ...
Blend multiple alpha forecasts into meta-models and portfolio signals, leveraging ensemble and Bayesian methods. * Develop portfolio construction and optimization techniques and analysis tools to be ...
Client Partner, TMT
New York, NY · On-site
... Bayesian modeling * Experience working with large-scale, high-volume datasets and partnering on modern data infrastructure with: * Cloud platforms: AWS, GCP, Azure * Data platforms: Snowflake ...
Client Partner, TMT
New York, NY · On-site
... Bayesian modeling * Experience working with large-scale, high-volume datasets and partnering on modern data infrastructure with: * Cloud platforms: AWS, GCP, Azure * Data platforms: Snowflake ...
Post-Doctoral Associate
$51K - $69K/yr
Experience with computational methods (e.g., Bayesian modeling, drift diffusion modeling, etc.) Equipment Utilized Physical Demands and Work Environment Overview Statement Posting Details Special ...
Post-Doctoral Associate
$51K - $69K/yr
Experience with computational methods (e.g., Bayesian modeling, drift diffusion modeling, etc.) Equipment Utilized Physical Demands and Work Environment Overview Statement Posting Details Special ...
Knowledge of advanced statistical methodologies, including regression, longitudinal analysis, and/or Bayesian modeling * Proficient in using Google Suite products or similar programs At this time ...
Knowledge of advanced statistical methodologies, including regression, longitudinal analysis, and/or Bayesian modeling * Proficient in using Google Suite products or similar programs At this time ...
Postdoctoral Associate (InfoCogLab)
New York, NY · On-site
$62K - $90K/yr
Strong background in working with computational models (such as deep learning models and/or Bayesian models) and strong programing skills. * Demonstrated ability to lead research projects and work ...
Postdoctoral Associate (InfoCogLab)
New York, NY · On-site
$62K - $90K/yr
Strong background in working with computational models (such as deep learning models and/or Bayesian models) and strong programing skills. * Demonstrated ability to lead research projects and work ...
Sr Software Engineer
Manhattan, NY · On-site
$134K - $177K/yr
... Bayesian model fitting, DSP, control systems • Constraint modeling frameworks (Pyomo) and commercial/open-source solvers (HiGHS, Gurobi, GLPK) • FastAPI and microservices experience • React for ...
Sr Software Engineer
Manhattan, NY · On-site
$134K - $177K/yr
... Bayesian model fitting, DSP, control systems • Constraint modeling frameworks (Pyomo) and commercial/open-source solvers (HiGHS, Gurobi, GLPK) • FastAPI and microservices experience • React for ...
Sr Software Engineer
New York, NY · On-site
$134K - $176K/yr
Energy experience and modeling, optimization * Experience with complex algorithm-driven problems: convex/constraint-based optimization problems, statistical modelling including Bayesian model fitting ...
Sr Software Engineer
New York, NY · On-site
$134K - $176K/yr
Energy experience and modeling, optimization * Experience with complex algorithm-driven problems: convex/constraint-based optimization problems, statistical modelling including Bayesian model fitting ...
Sr Software Engineer
$134K - $176K/yr
Energy experience and modeling, optimization * Experience with complex algorithm-driven problems: convex/constraint-based optimization problems, statistical modelling including Bayesian model fitting ...
Sr Software Engineer
$134K - $176K/yr
Energy experience and modeling, optimization * Experience with complex algorithm-driven problems: convex/constraint-based optimization problems, statistical modelling including Bayesian model fitting ...
Sr Software Engineer
New York, NY · On-site
$134K - $176K/yr
Energy experience and modeling, optimization * Experience with complex algorithm-driven problems: convex/constraint-based optimization problems, statistical modelling including Bayesian model fitting ...
Quick apply
Sr Software Engineer
New York, NY · On-site
$134K - $176K/yr
Energy experience and modeling, optimization * Experience with complex algorithm-driven problems: convex/constraint-based optimization problems, statistical modelling including Bayesian model fitting ...
Staff AI Scientist
New York, NY · On-site
$209K - $283K/yr
In this role you will be building and deploying machine learning models using both analytical ... Bayesian Learning, Reinforcement Learning, or Deep Learning) to real-world problems and datasets.
Staff AI Scientist
New York, NY · On-site
$209K - $283K/yr
In this role you will be building and deploying machine learning models using both analytical ... Bayesian Learning, Reinforcement Learning, or Deep Learning) to real-world problems and datasets.
Staff AI Scientist
Manhattan, NY · On-site
$209K - $283K/yr
In this role you will be building and deploying machine learning models using both analytical ... Bayesian Learning, Reinforcement Learning, or Deep Learning) to real-world problems and datasets.
Staff AI Scientist
Manhattan, NY · On-site
$209K - $283K/yr
In this role you will be building and deploying machine learning models using both analytical ... Bayesian Learning, Reinforcement Learning, or Deep Learning) to real-world problems and datasets.
Staff AI Scientist
Manhattan, NY · On-site
$10/hr
In this role you will be building and deploying machine learning models using both analytical ... Bayesian Learning, Reinforcement Learning, or Deep Learning) to real-world problems and datasets.
Staff AI Scientist
Manhattan, NY · On-site
$10/hr
In this role you will be building and deploying machine learning models using both analytical ... Bayesian Learning, Reinforcement Learning, or Deep Learning) to real-world problems and datasets.
... e.g., bayesian pooling, hierarchical modeling) * Demonstrated communication skills and experience presenting complex findings to both technical and non-technical stakeholders * Demonstrated ...
... e.g., bayesian pooling, hierarchical modeling) * Demonstrated communication skills and experience presenting complex findings to both technical and non-technical stakeholders * Demonstrated ...
Senior Machine Learning Engineer
New York, NY · On-site
$125K - $150K/yr
You will move beyond simple predictive models to build transformative algorithmic solutions using Bayesian Black Box optimization, Contextual Bandits, and Deep Q-Networks (DQN/DDQN). The problem ...
Senior Machine Learning Engineer
New York, NY · On-site
$125K - $150K/yr
You will move beyond simple predictive models to build transformative algorithmic solutions using Bayesian Black Box optimization, Contextual Bandits, and Deep Q-Networks (DQN/DDQN). The problem ...
Applied Scientist III - AMZ27579.1
New York, NY · On-site
$183K - $248K/yr
Bayesian models and deep neural networks), optimization methods, and other ML techniques to different applications in business and engineering. Routinely build and deploy ML models on available data ...
Applied Scientist III - AMZ27579.1
New York, NY · On-site
$183K - $248K/yr
Bayesian models and deep neural networks), optimization methods, and other ML techniques to different applications in business and engineering. Routinely build and deploy ML models on available data ...
Strong modeling and experimentation skills (Python, SQL, Bayesian / probabilistic modeling). * Comfort operating with limited data - capable of building and validating proxy-based models. * Blend of ...
Strong modeling and experimentation skills (Python, SQL, Bayesian / probabilistic modeling). * Comfort operating with limited data - capable of building and validating proxy-based models. * Blend of ...
... data models, metrics, and entity mapping (e.g., company/product/provider mapping, time-series ... Bayesian inference, regression, experimental design / quasi-experimental thinking). • Experience ...
... data models, metrics, and entity mapping (e.g., company/product/provider mapping, time-series ... Bayesian inference, regression, experimental design / quasi-experimental thinking). • Experience ...
Bayesian Modeling information
What is the difference between Bayesian Modeling vs Data Scientist?
| Aspect | Bayesian Modeling | Data Scientist |
|---|---|---|
| Required Credentials | Statistics, Mathematics, Data Analysis | Statistics, Computer Science, Data Analysis |
| Work Environment | Research-focused, statistical modeling | Cross-functional, data analysis, visualization |
| Industry Usage | Research, academia, specialized analytics | Business, tech, finance, healthcare |
| Common Search/Comparison | Yes | Yes |
Bayesian Modeling and Data Scientists often overlap in skills like statistics and data analysis. Bayesian Modeling specializes in probabilistic models and statistical inference, while Data Scientists have broader roles including data cleaning, visualization, and machine learning. Both roles are essential in data-driven industries, but Bayesian Modeling is more focused on advanced statistical techniques.
What are the key skills and qualifications needed to thrive as a Bayesian Modeler, and why are they important?
To thrive as a Bayesian Modeler, you need a solid background in statistics, probability theory, and mathematical modeling, often supported by an advanced degree in statistics, mathematics, or a related field. Proficiency with programming languages such as R, Python, or Stan, and experience with statistical software and Bayesian inference tools are essential. Strong analytical thinking, attention to detail, and effective communication skills help in interpreting results and collaborating with multidisciplinary teams. These skills ensure accurate model development, reliable data-driven insights, and clear communication of complex findings to stakeholders.
How does a Bayesian Modeling specialist typically collaborate with cross-functional teams in a workplace setting?
Bayesian Modeling specialists often work closely with data scientists, software engineers, and domain experts to integrate probabilistic models into larger analytical or production systems. They are involved in translating complex statistical concepts into actionable insights and recommendations tailored to business needs. Effective communication is key, as they must present findings to both technical and non-technical stakeholders, ensuring that model assumptions and results are clearly understood. Collaboration may also include contributing to code reviews, sharing best practices for model validation, and mentoring colleagues on Bayesian methodologies.
What is Bayesian modeling?
Bayesian modeling is a statistical approach that uses Bayes' Theorem to update the probability of a hypothesis as more data becomes available. It incorporates prior beliefs or knowledge, combines them with observed data, and produces a posterior probability distribution to guide inference and decision-making. This approach is widely used in various fields such as machine learning, data science, and scientific research for tasks like parameter estimation, prediction, and model selection.
What are popular job titles related to Bayesian Modeling jobs in New York? For Bayesian Modeling jobs in New York, the most frequently searched job titles are:
What job categories do people searching Bayesian Modeling jobs in New York look for? The top searched job categories for Bayesian Modeling jobs in New York are:
What cities in New York are hiring for Bayesian Modeling jobs? Cities in New York with the most Bayesian Modeling job openings:
Full-time
Re-posted 27 days ago
M&T Bank rating
7.8
Based on 183 frontline employees who took The Breakroom Quiz
76th of 149 rated banks
Job description
** Work Location/Arrangement: This is a hybrid position requiring in-office work four (4) days every week at an M&T office in Buffalo, NY, Bridgeport, CT, Wilmington, DE, Baltimore, MD, Boston, MA, or Metro NYC.
**If the final candidate is not near one of the above referenced locations, there might be a possibility for a remote arrangement.
OVERVIEW:
Manages and builds systems of models to analyze diverse big data sources to generate insights and solutions for business partners and product enhancement. Manages and participates in developing, testing and validating models that drive business value. Assists with identifying and interpreting insights from data. Direct leadership of assigned data science team.
POSITION RESPONSIBILITIES:
SPECIFIC TO POSTING:
MANAGERIAL/SUPERVISORY RESPONSIBILITY:
Number of Staff: 6-8
MINIMUM QUALIFICATIONS REQUIRED:
IDEAL QUALIFICATIONS PREFERRED:
M&T Bank is committed to fair, competitive, and market-informed pay for our employees. The pay range for this position is $150,800.00 - $251,300.00 Annual (USD). The successful candidate's particular combination of knowledge, skills, and experience will inform their specific compensation.
Location
New York, New York, United States of America
**If the final candidate is not near one of the above referenced locations, there might be a possibility for a remote arrangement.
OVERVIEW:
Manages and builds systems of models to analyze diverse big data sources to generate insights and solutions for business partners and product enhancement. Manages and participates in developing, testing and validating models that drive business value. Assists with identifying and interpreting insights from data. Direct leadership of assigned data science team.
POSITION RESPONSIBILITIES:
- Manage and participate in working with large data sets to solve unstructured problems using different analytical and statistical approaches for a single domain.
- Manage and participate in sourcing, ingesting, and cleaning of data sets in preparation for analysis, work with data teams to productionize and scale data cleanup process. Ensure data is stable, accounting for complex data drift in development and production.
- Manage and participate in the building of econometric, statistical and machine learning models for various problems inclusive of classification, clustering, pattern analysis, sampling, and simulations.
- Manage committing of complex coding into model repository to serve as a source for others and promote complex models into production system.
- Manage and develop champion/challenger models and adjust models accordingly.
- Manage, develop and implement framework for building self-healing models.
- Lead the selection and refinement of models taking into account performance, reliability and stability metrics and business feedback.
- Develop model refinement educational materials and deliver related training for data users.
- Guide less experienced data scientists on model development, selection, refinement, measurements, and visualizations and creating consumable model outputs.
- Create outputs from multiple models for business discussions to display model outcomes, impact and business value.
- Lead stakeholder meetings to discuss concerns, opportunities and production challenges.
- Work with more experienced data scientists to develop new research approaches, provide recommendations on how techniques will be adapted based on client needs, and attend meetings with data clients to understand their research questions.
- Review own and assigned team's code to ensure it is efficient, accurate, and using best practices.
- Exercise usual authority of a manager concerning staffing, performance appraisals, promotions, salary recommendations, performance management and terminations.
- Understand and adhere to the Company's risk and regulatory standards, policies and controls in accordance with the Company's Risk Appetite. Design, implement, maintain and enhance internal controls to mitigate risk on an ongoing basis. Identify risk-related issues needing escalation to management.
- Promote an environment that supports belonging and reflects the M&T Bank brand.
- Maintain M&T internal control standards, including timely implementation of internal and external audit points together with any issues raised by external regulators as applicable.
- Complete other related duties as assigned.
SPECIFIC TO POSTING:
- Oversee the development of complex analysis and judgment-based work to support the identification and quantification of compliance risk.
- Utilize a data driven approach to assess the effectiveness of risk controls, identifying exceptions and investigating root cause.
- Produce efficient, automated self-service solutions that empower non-technical stakeholders to derive data-driven insights and conclusions
- Work with business units and compliance groups to ensure consistent understanding of requirements.
- Execute independent assignments within defined timelines with attention to detail and an investigative, quality-first mindset
MANAGERIAL/SUPERVISORY RESPONSIBILITY:
Number of Staff: 6-8
MINIMUM QUALIFICATIONS REQUIRED:
- Bachelor's degree and a minimum of 7 years related experience, or in lieu of a degree, a combined minimum of 11 years higher education and/ or work experience, including a minimum of 7 years related experience
- Minimum of 2 years managerial, supervisory and/or work leadership experience
- Intermediate experience working with multiple statistics and following data science principles such as AB testing, sample selection, hypothesis testing, and modeling bias
- Intermediate proficiency with pertinent statistical software and languages and tools
- Experience with various hybrid databases both on premise and in the cloud
- Intermediate level knowledge of Structured Query Language (SQL) and Not Only Structured Query Language (nSQL)
- Expert understanding of modeling techniques such as Bayesian modeling, Classification models, Cluster analysis, Neural Network, Non-parametric methods, and Multivariate statistics
- Experience analyzing large data sets
IDEAL QUALIFICATIONS PREFERRED:
- Masters' of Science or Doctorate degree in Statistics, Economics, Finance or related field in the quantitative social, physical or engineering sciences, with proven coursework proficiency in statistics, econometrics, economics, computer science, finance or risk management
- Fluent in econometric/statistical techniques, including time-series analysis, panel data methods and logistic regression
- Tactical experience with pertinent statistical software and languages and tools
M&T Bank is committed to fair, competitive, and market-informed pay for our employees. The pay range for this position is $150,800.00 - $251,300.00 Annual (USD). The successful candidate's particular combination of knowledge, skills, and experience will inform their specific compensation.
Location
New York, New York, United States of America
About M&T Bank
Sourced by ZipRecruiter
Industry
Finance and insurance
Company size
10,000+ Employees
Headquarters location
Buffalo, NY, US
Year founded
1856