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Remote Behavioral Data Science Jobs in Austin, TX

SpyCloud

Senior Data Scientist, Applied ML

Austin, TX · On-site +1

$154K - $200K/yr

... for a Senior Data Scientist, Applied ML to design, build, and deploy models for critical ... In addition to our engaging workspace in South Austin, flexible and remote-friendly work options ...

RWE

Sr Product Manager, AI Transformation

Austin, TX · On-site +1

$160K - $200K/yr

Working knowledge of AI/ML concepts, data science workflows, generative AI, and emerging agentic ... If you currently have a remote exception or are not located in one of these markets, please confirm ...

SpyCloud

Data Processing Engineer

Austin, TX · On-site +1

$111K - $144K/yr

We are also open to candidates who are remote in the United States, but can travel to our ... Strong understanding of computer science fundamentals (data structures, algorithms, data processing)

YO AI Labs

AI Consulting Expert - Remote

Austin, TX · Remote

$100 - $200/hr

Remote Job Overview We are seeking experienced AI Consulting Domain Experts to contribute their ... Annotate data, interpret findings, and perform fact-checking to ensure high-quality content.

Civitech

Data Acquisition Specialist

Austin, TX · On-site +1

Civitech is a remote-first company hiring within our current footprint of 27 states (AL, AK, CA, CO ... Our rigorous approach to product design, testing, and data science leads to accurate assessments of ...

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Remote Behavioral Data Science information

See Austin, TX salary details

$41.1K

$141.2K

$199.2K

How much do remote behavioral data science jobs pay per year?

As of Sep 6, 2026, the average yearly pay for remote behavioral data science in Austin, TX is $141,208.00, according to ZipRecruiter salary data. Most workers in this role earn between $117,500.00 and $165,000.00 per year, depending on experience, location, and employer.

What is remote behavioral data science?

Remote behavioral data science is a field where professionals analyze and interpret data related to human behavior, often using statistical methods, machine learning, and data visualization, all while working from a remote location. These scientists work with data from sources such as online interactions, surveys, or sensors to uncover insights into patterns, preferences, and decision-making. Remote roles allow for flexibility and collaboration with teams and clients around the world, using digital tools for communication and data analysis. This field is interdisciplinary, drawing from psychology, data science, and computer science.

What are the key skills and qualifications needed to thrive as a remote behavioral data scientist?

To thrive as a Remote Behavioral Data Scientist, you need expertise in statistical analysis, machine learning, behavioral science, and a degree in a related field such as psychology, statistics, or computer science. Proficiency with data analysis tools like Python, R, SQL, and experience with data visualization platforms and cloud-based collaboration systems are typically required. Strong communication, critical thinking, and self-motivation are vital soft skills for presenting findings and working independently within remote teams. These skills ensure effective analysis of human behavior data, actionable insights, and successful collaboration in distributed work environments.

How do remote behavioral data scientists typically collaborate with cross-functional teams to drive impactful insights?

Remote behavioral data scientists regularly work with cross-functional teams such as product managers, UX researchers, and engineers to translate user data into actionable recommendations. Collaboration often happens via virtual meetings, shared dashboards, and project management tools, ensuring alignment on goals and data interpretations. Effective communication and documentation are crucial, as data scientists must clearly explain complex analyses and behavioral patterns to non-technical stakeholders. This collaborative environment not only fosters innovation but also ensures that data-driven insights meaningfully inform product and business decisions.

What are the most commonly searched types of Behavioral Data Science jobs in Austin, TX?

The most popular types of Behavioral Data Science jobs in Austin, TX are:

What are popular job titles related to Remote Behavioral Data Science jobs in Austin, TX?

For Remote Behavioral Data Science jobs in Austin, TX, the most frequently searched job titles are:

What job categories do people searching Remote Behavioral Data Science jobs in Austin, TX look for?

The top searched job categories for Remote Behavioral Data Science jobs in Austin, TX are:

What cities near Austin, TX are hiring for Remote Behavioral Data Science jobs?

Cities near Austin, TX with the most Remote Behavioral Data Science job openings:

Remote Behavioral Data Science jobs near you
Infographic showing various Remote Behavioral Data Science job openings in Austin, TX as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $141,208 per year, or $67.9 per hour.

Principal Data Engineer - Neo4J

Citizens Bank

Austin, TX • On-site, Remote

Full-time

Re-posted 11 days ago

Job description


Principal Data Engineer - Graph Data Engineering Neo4j
Role Summary
As Principal Data Engineer, you will be chartered with developing functional systems to realize key business objectives and goals, with a specialization in graph data engineering and connected data architecture. You will help lead a team of data engineers as you create interfaces, graph models, and data platforms that facilitate the flow, linkage, and contextualization of information across Citizens' business operations.
In this role, you will establish and scale graph-based solutions using Neo4j, enabling relationship-driven insights, network analytics, and advanced data discovery across domains such as fraud detection, risk analysis, and customer intelligence.
Specialized Responsibilities
  • Serve as a key contributor in designing and delivering graph data solutions, partnering with stakeholders to translate business needs into connected data models and graph architectures
  • Engineer and maintain graph database Neo4j, alongside relational and non-relational systems to support hybrid data environments
  • Develop and operationalize relationship-based data models, including nodes, edges, and properties aligned to enterprise business domains
  • Design and implement knowledge graphs and connected data platforms that unify disparate data sources and expose relationships across systems
  • Build and optimize graph ingestion pipelines for batch and streaming data sources, ensuring data freshness and integrity
  • Develop mechanisms and architectures that support business line specific use cases
  • Establish standards and best practices for graph modeling, schema evolution, and governance within the enterprise data ecosystem
  • Review and manage interfaces supporting graph data access including APIs, visualization tools, and analytics platforms
  • Partner with data science and analytics teams to enable graph-based feature engineering and machine learning integration

Preferred Technical Expertise
  • Deep expertise in Neo4j platform capabilities, including clustering, security, and enterprise deployment patterns
  • Experience in graph data modeling and ontology design for complex enterprise datasets
  • Knowledge of connected data architecture patterns, including knowledge graphs and data fabrics
  • Experience integrating graph platforms with big data ecosystems (Spark, Kafka, etc.) and cloud-native services
  • Strong understanding of query optimization, indexing, and graph performance tuning
  • Experience with data ingestion frameworks supporting both batch and real-time pipelines
  • Proficiency in Python

Business Outcomes and Impacts
  • Enable enhanced fraud detection and prevention through network-based analysis of entities, transactions, and behaviors
  • Accelerate Customer 360 insights by linking fragmented data across business domains
  • Support real-time decisioning through connected data models and optimized graph queries
  • Drive improved data integrity and lineage visibility through network-based representations
  • Enable faster, more scalable delivery of insight-driven business capabilities through reusable graph models

Preferred Qualifications
  • 8+ years of experience in data engineering, including experience leading engineers and technical teams
  • Proven experience implementing Neo4j in enterprise environments
  • Familiarity with machine learning and AI techniques leveraging graph data
  • Experience working in Agile environments and leading cross-functional delivery teams
  • Experience with visualization and BI tools in conjunction with graph-derived insights

Modernization and Architecture Expectations
  • Advance the organization's data architecture toward connected, relationship-driven models, complementing existing data platforms
  • Establish graph-first design patterns where relationship complexity drives business value
  • Integrate Neo4j into the broader enterprise data ecosystem (cloud, lakehouse, streaming platforms)
  • Promote adoption of knowledge graphs and semantic modeling to improve interoperability and reuse
  • Implement scalable, resilient graph data platforms aligned to enterprise security and compliance standards
  • Standardized graph engineering practices, including modeling guidelines, performance tuning, and operational monitoring
  • Partner with architecture leadership to define the future-state connected data vision, ensuring alignment with digital and AI strategies

About Us
Equal Employment Opportunity
Citizens, its parent, subsidiaries, and related companies (Citizens) provide equal employment and advancement opportunities to all colleagues and applicants for employment without regard to age, ancestry, color, citizenship, physical or mental disability, perceived disability or history or record of a disability, ethnicity, gender, gender identity or expression, genetic information, genetic characteristic, marital or domestic partner status, victim of domestic violence, family status/parenthood, medical condition, military or veteran status, national origin, pregnancy/childbirth/lactation, colleague's or a dependent's reproductive health decision making, race, religion, sex, sexual orientation, or any other category protected by federal, state and/or local laws. At Citizens, we are committed to fostering an inclusive culture that enables all colleagues to bring their best selves to work every day and everyone is expected to be treated with respect and professionalism. Employment decisions are based solely on merit, qualifications, performance and capability.
Equal Employment and Opportunity Employer
Job Applicant Data Privacy Policy
Background Check
Any offer of employment is conditioned upon the candidate successfully passing a background check, which may include initial credit, motor vehicle record, public record, prior employment verification, and criminal background checks. Results of the background check are individually reviewed based upon legal requirements imposed by our regulators and with consideration of the nature and gravity of the background history and the job offered. Any offer of employment will include further information.

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