ZipRecruiter

Log In

1

Data Science Contract Jobs in Riverside, CA (NOW HIRING)

Hyundai Capital

Sr. AI Governance Manager

Irvine, CA

$135K - $179K/yr

Partner with Legal/Security on vendor risk, contracts, and incident response. Work with cross-functional teams, including engineers, data scientists, and product managers to integrate AI governance ...

FieldAI

Data Platform Engineer, Data Pipelines

Irvine, CA · On-site

$122K - $147K/yr

Own integration reliability end to end: schema contracts, versioning, retries, backfills, and ... Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field. * 3 ...

New

FieldAI

Data Platform Engineer, Data Pipelines

Irvine, CA · On-site

$122K - $147K/yr

Own integration reliability end to end: schema contracts, versioning, retries, backfills, and ... Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field. * 3 ...

New

FieldAI

Data Platform Engineer, Data Pipelines

Irvine, CA · On-site

$122K - $147K/yr

Own integration reliability end to end: schema contracts, versioning, retries, backfills, and ... Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field. * 3 ...

New

FieldAI

Data Platform Engineer, Autonomy Analytics

Irvine, CA · On-site

$122K - $147K/yr

Own integration reliability end to end: schema contracts, versioning, retries, backfills, and ... What You Have * Bachelor's or Master's degree in Computer Science, Engineering, or a related ...

New

FieldAI

Data Platform Engineer, Autonomy Analytics

Irvine, CA · On-site

$122K - $147K/yr

Own integration reliability end to end: schema contracts, versioning, retries, backfills, and ... What You Have * Bachelor's or Master's degree in Computer Science, Engineering, or a related ...

New

CYNET SYSTEMS

Senior AI Engineer

Irvine, CA · On-site

$56 - $61/hr

Define best practices for API contracts, reliability, and enable reusability of platform ... Bachelor's or Master's degree in Computer Science, Data Science, AI, or a related field. * Proven ...

MDAEdge

Senior Director - FP&A Systems

Irvine, CA · On-site

... partner with data science teams to productionize AI solutions with robust governance and ... contracts, and budgets (OpEx/CapEx), optimizing total cost of ownership while mitigating risk. • ...

Prescient Edge

Senior Scientist

Riverside, CA · On-site

$95K - $130K/yr

Please note that the availability of this position is contingent upon contract award. Benefits: At ... Support data analysis efforts related to sensor inputs, surveillance systems, and operational ...

EKN Engineering

Business Analyst

Irvine, CA

Experience supporting proposal development, RFP responses, and contract pursuits. * Assist in ... Bachelor's degree in a relevant field (e.g., Data Science, Statistics, Computer Science) or ...

PacSun

Manager, Business Intelligence

Anaheim, CA · On-site

Manage a team of BI developers and data engineers (3-5 people) and contract resources. Provide ... Qualifications & Requirements Education Bachelor's degree in Information Systems, Computer Science ...

next page

Showing results 1-20

All JobsData Science Contract JobsData Science Contract Jobs in Riverside, CA

Data Science Contract information

See Riverside, CA salary details

$23.7K

$111.9K

$206.9K

How much do data science contract jobs pay per year?

As of Jul 12, 2026, the average yearly pay for data science contract in Riverside, CA is $111,880.00, according to ZipRecruiter salary data. Most workers in this role earn between $57,015.00 and $156,919.00 per year, depending on experience, location, and employer.

What is a Data Science Contract job?

A Data Science Contract job is a temporary or project-based role where a data scientist is hired for a specific period to work on data-related tasks such as analysis, machine learning, or model development. These roles can be short-term (a few months) or long-term but lack the benefits and job security of full-time employment. Contract data scientists often work with multiple clients, bringing expertise to solve business problems without a long-term commitment.

What kinds of projects and day-to-day tasks can I expect as a Data Science Contract professional?

As a Data Science Contract professional, you can expect to work on a variety of projects such as developing predictive models, analyzing large datasets, creating data visualizations, or advising organizations on best practices for data-driven decision making. Your day-to-day tasks may involve collaborating closely with clients or internal stakeholders to clarify objectives, cleaning and preparing data, developing algorithms, and presenting your findings in clear, actionable formats. Projects often vary in length and scope, offering exciting opportunities to tackle new business challenges across different industries. Flexibility and effective time management are essential, as balancing project deadlines and adapting quickly to new tools or domains are common aspects of contract-based work.

What are the key skills and qualifications needed to thrive in the Data Science Contract position, and why are they important?

To thrive as a Data Science Contract professional, you need a strong foundation in statistical analysis, machine learning, data manipulation, and advanced proficiency in programming languages such as Python or R, typically supported by a relevant degree. Experience with data visualization tools, cloud platforms, and certifications like AWS Certified Data Analytics or Microsoft Certified: Data Scientist are highly valued. Excellent communication, problem-solving abilities, and adaptability are crucial soft skills for collaborating with diverse teams and interpreting client needs. These skills ensure that contract-based data scientists can deliver actionable insights, adapt to new environments, and effectively address client-specific problems within limited project timelines.

What are the most commonly searched types of Data Science jobs in Riverside, CA? The most popular types of Data Science jobs in Riverside, CA are:
What are popular job titles related to Data Science Contract jobs in Riverside, CA? For Data Science Contract jobs in Riverside, CA, the most frequently searched job titles are:
What job categories do people searching Data Science Contract jobs in Riverside, CA look for? The top searched job categories for Data Science Contract jobs in Riverside, CA are:
What cities near Riverside, CA are hiring for Data Science Contract jobs? Cities near Riverside, CA with the most Data Science Contract job openings:
Data Science Contract jobs near you
Infographic showing various Data Science Contract job openings in Riverside, CA as of July 2026, with employment types broken down into 1% As Needed, 65% Full Time, 19% Part Time, 1% Temporary, and 14% Contract. Highlights an 81% Physical, 2% Hybrid, and 17% Remote job distribution, with an average salary of $111,880 per year, or $53.8 per hour.

Senior AI Engineer (GenAI and Data Platform - AWS)

Saransh Inc

Irvine, CA • On-site

$131K - $173K/yr

Contractor

Posted 24 days ago

Job description

Role: Senior AI Engineer (GenAI + Data Platform – AWS)
Location: 4 days a week onsite is must (3 days in Irvine, CA & 1 Day in Downtown, LA, CA)
Job Type: Contract

Role Summary:
  • We are seeking a Senior AI Engineer to design, build, and scale a production-grade Generative AI and Data Platform on AWS.
  • The role focuses on enabling LLM-powered capabilities through vector search, graph-based knowledge systems, and governed data pipelines.
Note:
Must Have Skills:
  • Generative AI / LLM (RAG, embeddings, prompt engineering)
  • AWS Cloud (OpenSearch, Neptune, DynamoDB, ElastiCache/Redis)
  • Vector Search & Retrieval Systems (OpenSearch / vector DB)
  • Graph Databases (Amazon Neptune, knowledge graphs)
  • LLM Frameworks (LangChain / LlamaIndex)
  • Agentic AI Frameworks (LangGraph / AutoGen / CrewAI)
  • Databricks & Apache Spark (data pipelines, embedding pipelines)
  • Backend/API Development (Python, scalable APIs, microservices)

Must Have Certifications:
AWS Certification (Preferred):
  • AWS Certified Solutions Architect OR
  • AWS Certified Machine Learning Specialty OR
  • AWS Data Engineer Certification

The ideal candidate will own end-to-end delivery across the AI lifecycle, including:
  • Data ingestion and knowledge curation
  • Embeddings and retrieval systems
  • Backend services and APIs
  • CI/CD pipelines and deployment
Key Responsibilities:
1. GenAI Enablement & Integration
 
Build and operationalize LLM-powered applications using:
  • Retrieval-Augmented Generation (RAG)
  • Embeddings pipelines
  • Prompt orchestration and evaluation frameworks
  • Design and implement vector search systems using Amazon OpenSearch
  • Develop graph-based knowledge systems using Amazon Neptune for relationships, lineage, and explainability
Integrate supporting infrastructure:
  • Amazon ElastiCache (Redis) for session state and caching
  • DynamoDB for scalable, low-latency data access
 
Implement agentic workflows using frameworks such as:
LangGraph, AutoGen, CrewAI (or equivalent)
Integrate with LLM frameworks like:
LangChain, LlamaIndex (tool calling, retrieval orchestration, context management)
Define standards for:
Tool integration
Context-sharing patterns (MCP-style designs)
Evaluate LLM models and retrieval strategies across:
Latency
Cost
Accuracy
Context limitations
 
2. Data Pipelines & Knowledge Engineering
Design and build scalable data pipelines using Databricks and Apache Spark
Implement:
  • Data ingestion and transformation pipelines
  • Document processing (chunking, metadata tagging)
  • Embedding generation and indexing
Ensure high data quality standards:
Validation, completeness, consistency, monitoring
 
Implement data governance frameworks:
  • Data classification and access controls
  • Retention policies
  • Auditability and lineage tracking
3. Backend Services & APIs
Develop backend services exposing AI capabilities through secure and scalable APIs
Define best practices for:
API contracts and versioning
Reliability (retry logic, circuit breakers, idempotency)
Enable reusability of platform capabilities across teams and applications.
 
4. Deployment, MLOps & Operational Excellence
Build and manage CI/CD pipelines for AI and data workloads
Deploy production systems using:
Docker (containerization)
Kubernetes (orchestration)
Implement deployment strategies:
Blue/green deployments
Canary releases
Rollback strategies
Feature flags
Ensure system reliability through:
Monitoring (latency, failures, cost, data freshness)
Alerting and observability
Secrets management and least-privilege access
Optimize platform performance and cost
 
5. LLM Observability, Evaluation & Quality
Define and track GenAI quality metrics:
Grounding / faithfulness
Retrieval relevance
Response consistency
Latency and cost per request
Implement:
Prompt/version tracking
Offline evaluation pipelines
Continuous improvement workflows
 
6. LLM Security, Safety & Compliance
Implement secure AI systems with:
Access control and authentication
Data protection policies
Responsible AI guardrails
Ensure compliance with best practices in:
AI safety
Data privacy
Monitoring and auditability
Required Skills:
  • Strong experience in Generative AI / LLM systems (RAG, embeddings, prompt engineering)
  • Hands-on experience with AWS ecosystem
Expertise in:
  • OpenSearch (vector search)
  • Neptune (graph databases)
  • DynamoDB and Redis (ElastiCache)
Experience with:
  • LangChain / LlamaIndex
  • Agentic AI frameworks (LangGraph, AutoGen, CrewAI)
  • Strong programming skills (Python preferred)
  • Experience with Databricks and Apache Spark
Solid understanding of:
  • Data pipelines
  • Distributed systems
  • API design
Preferred Skills:
Experience with:
  • Model evaluation frameworks and LLM observability tools
  • AI governance and compliance frameworks
  • Kubernetes and advanced MLOps practices
Familiarity with:
  • Model Context Protocol (MCP) patterns
  • Agent-based architectures
Qualifications:
  • Bachelor’s or Master’s degree in: Computer Science / Data Science / AI / related field
  • Proven experience building production-grade AI platforms and systems
  • Strong background in end-to-end AI/ML lifecycle delivery.