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Behavioral Data Science Jobs in New York (NOW HIRING)

Citigroup, Inc.

VP Marketing Data Science

New York, NY · On-site

... behavior, conduct and business practices, and escalating, managing and reporting control issues ... data science libraries and frameworks. * Experience with big data technologies, cloud platforms ...

American Express

Manager-Data Science

Manhattan, NY · On-site

$103K - $174K/yr

... Data Science, Advanced Analytics, Machine Learning, Decision Science, or Customer Analytics ... Leadership Behaviors, and an unwavering commitment to back our customers, communities, and ...

Citigroup, Inc.

SVP Marketing Data Science

New York, NY · On-site

... behavior, conduct and business practices, and escalating, managing and reporting control issues ... data science libraries and frameworks. * Experience with big data technologies, cloud platforms ...

Melotech

Data Science, Music & Audio

New York, NY · On-site

Analyzing trends, audience behavior, and performance metrics to guide business decisions Who you are We look for battle-tested data scientists who understand that real impact comes from turning messy ...

Verizon

Principal Data Science Engineer

Basking Ridge, NJ · On-site

$118K - $141K/yr

Data science is the engine that drives informed decision-making and unlocks the hidden potential ... customer behaviors and market trends for the Verizon Consumer Group. You will use data and ...

Bedrock Robotics

Data Scientist

New York, NY · On-site

Bedrock Robotics is hiring a Data Scientistto lead high-impact data science work across autonomy ... Define and track key metrics that measure system behavior and product outcomes * Design and ...

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Showing results 21-40

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Behavioral Data Science information

See New York salary details

$26.2K

$117.4K

$218.7K

How much do behavioral data science jobs pay per year?

As of Aug 8, 2026, the average yearly pay for behavioral data science in New York is $117,391.00, according to ZipRecruiter salary data. Most workers in this role earn between $67,236.00 and $159,617.00 per year, depending on experience, location, and employer.

What can I do with a behavioral data science degree?

A behavioral data science degree prepares individuals for roles such as data analyst, behavioral scientist, or user experience researcher, focusing on analyzing human behavior through data. Graduates often work with statistical tools, programming languages like Python or R, and data visualization software to inform decision-making in marketing, product development, or healthcare. These roles typically require strong analytical skills and understanding of psychological or social science principles.

What does a behavioral data scientist do?

A behavioral data scientist analyzes data related to human behavior to identify patterns and insights that can inform decision-making. They use statistical methods, machine learning, and data visualization tools to interpret complex datasets and often work with psychology, marketing, or product teams to improve user engagement and outcomes.

What is behavioral data science?

A Behavioral Data Science job focuses on analyzing human behavior using data-driven techniques from psychology, economics, and machine learning. Professionals in this field work with large datasets to understand, predict, and influence decision-making patterns. They apply statistical models, AI, and behavioral theories to areas like marketing, finance, healthcare, and policy-making. The role typically involves data collection, analysis, and interpretation to optimize user experiences and business strategies.

What types of projects or problems do behavioral data scientists typically work on?

Behavioral Data Scientists often tackle projects that involve analyzing patterns in user behavior, identifying factors that drive engagement, or developing predictive models related to decision-making. They may work on optimizing customer experiences, evaluating the effectiveness of behavioral interventions, or supporting product teams with data-driven insights. The role frequently involves collaborating with psychologists, UX researchers, and business strategists to integrate behavioral data into broader company goals. This work requires both technical analysis and the ability to communicate findings to diverse stakeholders.

Is behavioral data science in high demand?

Behavioral data science is in high demand as organizations seek to understand human behavior through data analysis, machine learning, and statistical modeling. Professionals with skills in programming, data visualization, and behavioral psychology are especially sought after across industries such as marketing, healthcare, and finance.

What are the key skills and qualifications needed to thrive in behavioral data science, and why are they important?

To thrive as a Behavioral Data Scientist, you need expertise in behavioral science, statistics, and data analysis, typically backed by an advanced degree in psychology, data science, or a related field. Familiarity with tools like Python, R, SQL, and data visualization platforms, as well as certifications in data analytics, is highly valued. Strong critical thinking, communication, and collaboration skills help you interpret complex data patterns and translate them into actionable insights. These abilities are crucial for effectively analyzing human behavior data and driving organizational decision-making.

What are the most commonly searched types of Behavioral Data Science jobs in New York? The most popular types of Behavioral Data Science jobs in New York are:
What are popular job titles related to Behavioral Data Science jobs in New York? For Behavioral Data Science jobs in New York, the most frequently searched job titles are:
What job categories do people searching Behavioral Data Science jobs in New York look for? The top searched job categories for Behavioral Data Science jobs in New York are:
What cities in New York are hiring for Behavioral Data Science jobs? Cities in New York with the most Behavioral Data Science job openings:
Behavioral Data Science jobs near you
Infographic showing various Behavioral Data Science job openings in New York as of August 2026, with employment types broken down into 63% Full Time, 31% Part Time, and 6% Contract. Highlights an 100% In-person job distribution, with an average salary of $117,391 per year, or $56.4 per hour.

Senior Data Scientist - Generative AI (Data Science Lab)

Spartan Technologies, Inc.

Manhattan, NY • On-site

Full-time

Re-posted 11 days ago

Job description

Senior Data Scientist (Generative AI), Data Science Lab
  • Direct Hire
  • Hybrid
  • Office locations: NYC, NY | Holmdel, NJ | Stamford, CT | Bethlehem, PA, Boston, MA

We are seeking a Senior Data Scientist - Generative AI to be a contributor with a strong background in LLM and Generative AI. You will be responsible developing advanced data science solutions, leveraging machine learning and artificial intelligence, to drive enterprise-wide innovation across various business lines and Company's products. You will collaborate with Data Science Tech Leads on high-impact high-visibility projects to deliver AI/ML solutions that will be market-tested and deployed to make a real difference to risk management and the Company's overall financial performance. Successful candidates bring expertise in insurance and financial services, a passion for applying cutting-edge ML and AI insights, and the ability to design and implement data science capabilities that foster growth, competitive advantage, and customer satisfaction.
You Will:
  • Develop Deep Learning/Large Language Model/Generative AI capabilities
    • Mapping and mining unstructured data such as insurance contracts, medical records, sale notes, and customer servicing logs
    • AI/ML solutions include but not limited to enhancing underwriting risk assessment, claims auto adjudication, and customer servicing
    • Run large-scale experiments, from unsupervised pre-training, to fine-tuning, retrieval augmentation and prompt engineering
    • Scaling LLM models both in development and in production
    • Design and develop high-quality prompts and templates that guide the behavior and responses of LLM. Craft prompts to elicit specific information or control the model's output, ensuring desired accuracy, relevance, and language fluency. Optimize prompts to improve user interactions and system performance
    • Evaluate LLM models on statistical tests, business metrics, and bias an other regulatory metrics
  • Develop Deep Learning/Large Language Model/Generative AI capabilities
    • Mapping and mining unstructured data such as insurance contracts, medical records, sale notes, and customer servicing logs
    • AI/ML solutions include but not limited to enhancing underwriting risk assessment, claims auto adjudication, and customer servicing
    • Run large-scale experiments, from unsupervised pre-training, to fine-tuning, retrieval augmentation and prompt engineering
    • Scaling LLM models both in development and in production
    • Design and develop high-quality prompts and templates that guide the behavior and responses of LLM. Craft prompts to elicit specific information or control the model's output, ensuring desired accuracy, relevance, and language fluency. Optimize prompts to improve user interactions and system performance
    • Evaluate LLM models on statistical tests, business metrics, and bias an other regulatory metrics
  • Develop Enterprise Test and Learn Capabilities
    • Investigating the current state of the art of experimentation practices and causal inferencing/ML techniques identifying opportunities for upscaling the methodology best practices
    • Develop and execute advanced data-driven experiments to optimize various aspects of Guardian's business
    • Creation of test hypothesis, experiment design including KPI selection, and collection and analysis of data
  • Support and help build the Data Science Lab (DSL)
    • Support use case development that includes initial data exploration, project/sample design, reception and processing of data, performing analysis and modeling to creation of final report/presentation
    • Data wrangling/data matching/ETL to explore a variety of data sources, gain data expertise, perform summary analyses and prepare modeling datasets
    • Utilizing advanced statistical and AI/ML techniques to create high-performing predictive models and creative analyses to address business objectives and partner needs
    • Identification of source data and data quality checks both in model/solution development and in production
    • Packaging of model/solution and deployment in cooperation with Data Engineers and MLOps
  • Contribute to the overall Data Science organization
    • Collaborate with cross-functional teams of other Data Science, Data Engineering, Business groups
    • Contribute to standardization of Data Science tools, processes, and best practices

You are:
Passionate about cutting-edge technology and keen on applying new AI/ML algorithms and approaches. You are analytically driven, intellectually curious, and experienced leading the development and implementation of data and analytic solutions to solve challenging business problems. You enjoy collaborating with other data scientists to crack hard to solve problems with AI/ML and seeing it deployed in-market and generating value for the Company. You enjoy collaborating with a multi-disciplinary team including data engineers, business analysts, software developers and functional business experts and business leaders.
You have:
  • PhD with 2+ years of experience, Master's degree with 4+ years of experience in Statistics, Computer Science, Engineering, Applied mathematics or related field
  • 3+ years of hands-on ML modeling/development experience
  • Strong theoretical foundations in probability & statistics, and causal inferencing techniques
  • Extensive experience in deep learning models including Large Language Models (LLM) and Natural Language Processing (NLP)
  • Hands-on experience with GPU, distributed computing and applying parallelism to ML solutions
  • Strong programming skills in Python including PyTorch and/or Tensorflow
  • Solid background in algorithms and a range of ML models
  • Excellent communication skills and ability to work and collaborating cross-functionally with Product, Engineering, and other disciplines at both the leadership and hands-on level
  • Excellent analytical and problem-solving abilities with superb attention to detail
  • Proven leadership in providing technical leadership and mentoring to data scientists and strong management skills with ability to monitor/track performance for enterprise success

Apply