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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 are popular job titles related to Probabilistic Programming Bayesian jobs in New York? For Probabilistic Programming Bayesian jobs in New York, the most frequently searched job titles 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 June 2026, with employment types broken down into 100% Full Time. Highlights an 50% In-person, and 50% Hybrid job distribution.
Data Scientist with Python expertise in New York

Data Scientist with Python expertise in New York

Capgemini

New York, NY • On-site

$100K - $130K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 4 days ago


Capgemini North America rating

7.7

Company rating: 7.7 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

81st of 204 rated it services


Job description

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you'd like, where you'll be supported and inspired by a collaborative community of colleagues around the world, and where you'll be able to reimagine what's possible. Join us and help the world's leading organizations unlock the value of technology and build a more sustainable, more inclusive world.
Onsite : New York
Job Description
Key Responsibilities
Attribution & Measurement Modeling
• Build and maintain multi-touch attribution (MTA) models - touch-order aware, channel-weighted, with incremental lift quantification across owned, paid, and clean room channels
• Develop cohort-level LTV/CAC scoring models using transaction signals, behavioral features (SHAP-ranked), and propensity scores - deployed at segment and micro-cohort resolution
• Design holdout and matched-market test frameworks for measuring incrementality across CTV, display, paid search, and social channels
• Build probabilistic identity linkage models for household graph construction and cross-device resolution where deterministic signals are absent
Audience Intelligence
• Develop SHAP-based feature importance pipelines for audience signal ranking - surfacing top predictive signals per segment for AI-generated audience briefs
• Build behavioral micro-cohort clustering using unsupervised and semi-supervised methods on transaction and lifestyle features - producing 10+ interpretable sub-cohorts per major audience segment
• Design suppression, exclusion, and lookalike model pipelines that feed into DSP activation and clean room audience delivery
AI Integration & Insight Generation
• Collaborate with engineering to design system prompts, structured output schemas, and evaluation frameworks for AI-powered audience authoring, measurement intelligence, and campaign brief generation
• Build model evaluation pipelines comparing AI-generated audience segments against held-out conversion actuals, benchmarking performance vs. deterministic baselines
• Develop geo-level DMA performance models: LTV/CAC opportunity mapping, state-vs-DMA benchmarking, and priority zone classification for campaign planning
• Author AI-assisted insight narratives - translating model outputs into plain-language recommendations surfaced to client marketing teams through the platform UI
Required Qualifications
• 5+ years applied data science experience
• Expert Python proficiency: scikit-learn, XGBoost or LightGBM, SHAP, pandas, statsmodels, and at least one deep learning framework for production model development
• Deep expertise in multi-touch attribution methodologies: MTA, media mix modeling (MMM), incrementality testing, and controlled experiment design
• Experience building LTV, propensity, and CAC models on financial transaction or behavioral data at segment and sub-segment resolution
• Comfort operating inside data clean rooms - designing models that run on privacy-preserving aggregates rather than individual-level raw data
• Strong statistical foundations: causal inference, Bayesian methods, survival analysis, and experiment design
• Fluent SQL across cloud data warehouses (Snowflake, BigQuery, Redshift, or equivalent) and experience working with ML platforms such as Vertex AI, SageMaker, or Databricks MLflow
• Ability to translate complex model outputs into business narratives for VP- and C-level marketing stakeholders
Preferred Qualifications
• Experience designing AI-augmented analytics workflows - using LLM APIs for structured output generation, signal summarization, or compliance pre-screening alongside traditional models
• Familiarity with walled garden measurement environments: Google ADH, Meta Analytics API, Amazon Attribution
• Graph-based modeling experience - using Neo4j, Amazon Neptune, or similar for identity linkage, co-purchase signals, or household relationship modeling
• Demonstrated expertise in identity resolution, household modeling, or cross-device attribution at scale'
The base compensation range for this role in the posted location is: $100000 to $130000
Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law.
The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction.
These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity.
It is not typical for candidates to be hired at or near the top of the posted compensation range.
In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws.
Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees. In the U.S. and Canada, available benefits are determined by local policy and eligibility and may include:
  • Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave
  • Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)
  • Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
  • Life and disability insurance
  • Employee assistance programs
  • Other benefits as provided by local policy and eligibility

Important Notice: Compensation (including bonuses, commissions, or other forms of incentive pay) is not considered earned, vested, or payable until it becomes due under the terms of applicable plans or agreements and is subject to Capgemini's discretion, consistent with applicable laws. The Company reserves the right to amend or withdraw compensation programs at any time, within the limits of applicable legislation.
Disclaimers
Capgemini is an Equal Opportunity Employer encouraging inclusion in the workplace. Capgemini also participates in the Partnership Accreditation in Indigenous Relations (PAIR) program which supports meaningful engagement with Indigenous communities across Canada by promoting fairness, accessibility, inclusion and respect. We value the rich cultural heritage and contributions of Indigenous Peoples and actively work to create a welcoming and respectful environment. All qualified applicants will receive consideration for employment without regard to race, national origin, gender identity/expression, age, religion, disability, sexual orientation, genetics, veteran status, marital status or any other characteristic protected by law.
This is a general description of the Duties, Responsibilities and Qualifications required for this position. Physical, mental, sensory or environmental demands may be referenced in an attempt to communicate the manner in which this position traditionally is performed. Whenever necessary to provide individuals with disabilities an equal employment opportunity, Capgemini will consider reasonable accommodations that might involve varying job requirements and/or changing the way this job is performed, provided that such accommodation does not pose an undue hardship. Capgemini is committed to providing reasonable accommodation during our recruitment process. If you need assistance or accommodation, please reach out to your recruiting contact.
Please be aware that Capgemini may capture your image (video or screenshot) during the interview process and that image may be used for verification, including during the hiring and onboarding process.
Click the following link for more information on your rights as an Applicant in the United States. http://www.capgemini.com/resources/equal-employment-opportunity-is-the-law
Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.

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