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Probabilistic Programming Bayesian Jobs in New York

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Probabilistic Programming Bayesian information

What are the typical challenges faced by professionals working in Probabilistic Programming with a Bayesian focus, and how can they be addressed?

Professionals working in Probabilistic Programming with a Bayesian focus often encounter challenges related to model complexity, computational efficiency, and communicating results to non-technical stakeholders. Building accurate Bayesian models requires careful selection of priors and an understanding of underlying data distributions, which can be demanding without robust domain expertise. Additionally, computational demands can be high, especially for large datasets or complex hierarchical models, making efficient sampling and approximation methods essential. Collaborating closely with domain experts and leveraging modern probabilistic programming frameworks can help address these challenges and ensure practical, interpretable results.

What is probabilistic programming in the context of Bayesian statistics?

Probabilistic programming in the context of Bayesian statistics refers to writing computer programs that use probability distributions and Bayesian inference to model uncertainty and learn from data. These programs allow users to define complex probabilistic models using code, making it easier to specify, fit, and analyze Bayesian models. Probabilistic programming languages, such as Stan, PyMC, or Edward, provide tools to automate inference, enabling practitioners to focus on modeling rather than mathematical derivations. This approach is widely used in fields like machine learning, data science, and scientific research to handle uncertainty and make predictions.

What is the difference between Probabilistic Programming Bayesian vs Data Scientist?

AspectProbabilistic Programming BayesianData Scientist
Required credentialsBackground in statistics, probability, programmingStatistics, computer science, or related degree
Work environmentResearch, modeling, algorithm developmentData analysis, visualization, business insights
Industry usageAI, machine learning, research projectsBusiness, finance, tech, healthcare

Probabilistic Programming Bayesian focuses on developing models using Bayesian methods and probabilistic programming languages, often in research or AI development. Data Scientists analyze data to extract insights, build predictive models, and support decision-making. While both roles require statistical knowledge, Bayesian programmers specialize in probabilistic modeling, whereas Data Scientists apply a broader set of data analysis techniques.

What are the key skills and qualifications needed to thrive as a Probabilistic Programming Bayesian specialist, and why are they important?

To thrive as a Probabilistic Programming Bayesian specialist, you need a strong background in statistics, probability theory, and Bayesian inference, often supported by a degree in mathematics, statistics, computer science, or a related field. Expertise with probabilistic programming languages (such as Stan, PyMC, or TensorFlow Probability) and familiarity with statistical modeling software are also essential. Analytical thinking, problem-solving, and effective communication skills help translate complex models into actionable insights and collaborate with interdisciplinary teams. These skills and qualities are crucial for developing robust, interpretable models that inform decision-making in research and industry applications.
What job categories do people searching Probabilistic Programming Bayesian jobs in New York look for? The top searched job categories for Probabilistic Programming Bayesian jobs in New York are:
What cities in New York are hiring for Probabilistic Programming Bayesian jobs? Cities in New York with the most Probabilistic Programming Bayesian job openings:
Infographic showing various Probabilistic Programming Bayesian job openings in New York as of July 2026, with employment types broken down into 100% Full Time. Highlights an 50% In-person, and 50% Hybrid job distribution.
Process Development Engineer III, AI and Data Science

Process Development Engineer III, AI and Data Science

Regeneron Pharmaceuticals, Inc.

Tarrytown, NY • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 12 days ago


Regeneron rating

8.7

Company rating: 8.7 out of 10

Based on 42 frontline employees who took The Breakroom Quiz

12th of 74 rated pharmaceutical


Job description

The Data Enablement and Analytics (DEA) team within the PAPD (Product, Analytics and Process Development) organization drives PAPD's digital transformation by making data usable, useful, and impactful in support of our mission of Transforming Therapeutic Molecules into Products for a Diversified Pipeline.
We are seeking a Process Development Engineer III, AI and Data Science to join our Artificial Intelligence (AI) and Advanced Analytics (AA) team in DEA, who pairs deep bioprocess-engineering expertise with sophisticated AI/ML and Data Science (DS) capabilities to accelerate biologics development and manufacturing.
You will design, implement, and operationalize AI and DS models for upstream (cell-culture/bioreactor), downstream (purification) operations, Formulation Development and multiple Analytics teams while partnering closely with process-development, manufacturing-sciences, and digital teams. You will turn data into prescriptive guidance, deploy production-grade models, and build innovative AI solutions that enhance process understanding, optimization, and automation.
A Typical Day in the Role of Process Development Engineer III Might Look Like:
  • Build and deploy AI/ML-powered solutions to accelerate our digitalization journey.
  • Advance PAPD's broader AI, DS and related digital-maturity initiatives.
  • Collaborate with process engineers, citizen data scientists, IT, and manufacturing colleagues to coordinate AI and Advanced modeling efforts enterprise wide.
  • Explore, prototype and implement GenAI approaches and solutions (e.g., Retrieval-Augmented Generation) to enhance knowledge management, and decision support.
  • Develop, validate, and maintain mechanistic, hybrid, and data-driven models for cell culture, purification, formulation and other processes. These include digital twins, advanced predictive modelling, and process control techniques.
  • Translate complex bioprocess questions into quantitative modeling strategies that inform scale-up, tech transfer, and continuous improvement.
  • Mentor citizen data scientists and champion best practices in model development, method selection, and code quality.

This Role Might Be For You If You Have:
  • Analytical rigor and creative problem solving
  • Ability to drive projects autonomously while thriving in cross-functional teams
  • Excellent written and verbal communication
  • Passion for innovation and continuous learning

Required Qualifications
  • This role requires a Ph.D. in Chemical/Biochemical Engineering, Biotechnology, Applied Mathematics, Computer Science or related field with 0-2+ years of industrial experience OR- Master's with 7+ years.
  • Expert programming proficiency in Python and experience with statistical/computational tools such as JMP, SIMCA or MATLAB is required.
  • Proven ability to communicate technical concepts to multidisciplinary stakeholders.

Preferred Qualifications
  • Hands-on experience with cloud analytics platforms (e.g., Dataiku, Databricks).
  • Strong working knowledge of Quality-by-Design (QbD) principles and statistically rigorous Design-of-Experiments (DoE) for defining design space, optimizing critical process parameters, and informing robust control strategies.
  • Familiarity with PAT and chemometric modeling (e.g., Raman spectroscopy) for bioprocess monitoring and control.
  • Understanding of operation research techniques such as combinatorial optimization, linear programming, mixed integer programming is a plus.
  • Ability to deal with data from both SQL and NoSQL systems to support analytics, real-time processing, and application performance is a plus.
  • Publication record in bioprocess modeling or AI for biomanufacturing is a plus.
  • Mechanistic understanding of upstream and/or downstream bioprocess unit operations, scale-up/down principles, and critical quality attributes is strongly preferred.
  • A demonstrated success modeling bioprocesses via first-principles, hybrid, or data-driven (ML) methods is preferred.
  • A strong foundation in AI/ML algorithms (regression, classification, Bayesian methods, deep learning, time-series, probabilistic modeling) is a plus, along with expertise in multivariate statistics for process modeling, real-time monitoring, and control.
  • Some experience with GenAI stacks (LLMs, vector databases, RAG pipelines) and multimodal techniques is necessary/required/strongly preferred.

Does this sound like you? Apply now to take your first step towards living the Regeneron Way! We are committed to building a workplace with an inclusive culture. Regeneron is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion or belief (or lack thereof), sex, sexual orientation, gender identity or expression, gender reassignment, marital or civil partnership status, civil status, pregnancy or parental status, age, disability, nationality, citizenship status, ethnic or national origin, membership of the Traveler community, familial status, genetic information, military or veteran status, or any other characteristic protected under applicable law. Where required, we will provide reasonable accommodation to applicants with known disabilities or chronic illnesses during the recruitment process, unless such accommodation would impose undue hardship.
Where necessary, we disclose salary ranges for roles in all countries in which we operate. The final offer will be determined within the relevant range based on the country of employment, specific role level, and your skills and experience. In some countries, collective bargaining agreements (CBAs) may apply and influence certain elements of pay or benefits. Regeneron offers a competitive and comprehensive total rewards package which may include, depending on country and role: annual bonuses or other incentive plans, equity awards, pension or retirement benefits, 401(k) company match, health and wellness programs, fitness centers, insurance benefits (e.g. medical, dental, vision, life and disability), paid time off, and family support benefits. For additional information about Regeneron benefits in the U.S., please visit https://careers.regeneron.com/en/working-at-regeneron/total-rewards/. For other locations, additional information will be provided during the recruitment process. If you have any questions, please speak with your recruiter.
Please be advised that at Regeneron, we believe we do our best work when we are together. For that reason, many roles are required to be performed on-site. Please speak with your recruiter and hiring manager for more information about on-site expectations for your role and location.
As part of the recruitment process, certain background checks may be conducted in accordance with the laws of the country where the position is based. The purpose of such checks is to verify certain information prior to the commencement of employment such as identity, right to work and educational qualifications.
For jobs in Canada: this posting is for an existing position.
Salary Range (annually)
$109,900.00 - $179,300.00

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