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Data Science Associate Jobs in Napa, CA (NOW HIRING)

Qcells

Lead Data Engineer

San Francisco, CA · On-site

$160K - $220K/yr

Azure certifications (Data Engineer Associate, Solutions Architect, or equivalent). * Experience enabling analytics teams, data science workflows, or ML pipelines. * Experience implementing ...

Osmind

Life Sciences Associate

San Francisco, CA

$110K - $125K/yr

Our Biosciences team turns that data and clinical footprint into partnerships with biopharma companies across our four life sciences product lines: clinical real-world evidence, clinical research ...

Dodgeandcox

Business Solutions Associate

San Francisco, CA · On-site

$95 - $160/hr

Associates will work on problems with real business consequences: mapping and redesigning manual ... One-year master's programs in AI, Data Science, Business Analytics, or related fields are strongly ...

Dodge & Cox

Business Solutions Associate

San Francisco, CA · On-site +1

$95K - $160K/yr

Associates will work on problems with real business consequences: mapping and redesigning manual ... One-year master's programs in AI, Data Science, Business Analytics, or related fields are strongly ...

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All JobsData Science Associate JobsData Science Associate Jobs in Napa, CA

Data Science Associate information

See Napa, CA salary details

$65.2K

$77.1K

$146.2K

How much do data science associate jobs pay per year?

As of Sep 6, 2026, the average yearly pay for data science associate in Napa, CA is $77,120.00, according to ZipRecruiter salary data. Most workers in this role earn between $66,900.00 and $67,400.00 per year, depending on experience, location, and employer.

What is a data science associate?

Data Science Associates are early-career professionals who support data-driven projects by collecting, cleaning, analyzing, and interpreting large datasets. They typically work under the guidance of more experienced data scientists and help build predictive models, generate reports, and provide insights to inform business decisions. This role often requires proficiency in programming languages like Python or R, familiarity with statistical methods, and strong problem-solving skills. Data Science Associates play a crucial part in transforming raw data into actionable information for organizations.

What are the key skills and qualifications needed to thrive as a data science associate?

To thrive as a Data Science Associate, you need strong analytical skills, a solid foundation in statistics and mathematics, and proficiency in programming languages like Python or R, often supported by a degree in data science, computer science, or a related field. Familiarity with machine learning frameworks, data visualization tools, and database systems such as SQL is typically required. Excellent problem-solving abilities, effective communication, and collaboration skills help you translate complex data insights into actionable business strategies. These skills are vital for extracting meaningful value from data and supporting data-driven decision-making within organizations.

How does a data science associate typically collaborate with other departments or teams within an organization?

Data Science Associates frequently work cross-functionally, partnering with teams such as engineering, product management, and business analytics to understand project requirements, share findings, and implement data-driven solutions. Collaboration often involves translating complex data results into actionable insights for non-technical stakeholders, ensuring alignment on project goals and deliverables. This role requires strong communication skills, as associates routinely participate in meetings, present analyses, and gather feedback to refine their models or analyses. Effective teamwork helps ensure that data science initiatives support broader business objectives.

What is the difference between Data Science Associate vs Data Analyst?

AspectData Science AssociateData Analyst
Required CredentialsBachelor's degree in Data Science, Statistics, or related field; some roles prefer certifications in data analysis or programmingBachelor's degree in Statistics, Mathematics, or related field; often no advanced certifications required
Work EnvironmentCollaborates with data scientists and engineers; involved in building models and algorithmsFocuses on data collection, cleaning, and reporting; supports decision-making
Employer & Industry UsageUsed in tech, finance, healthcare, and consulting firms for data-driven projectsCommon across various industries for business insights and reporting

The Data Science Associate role typically involves more technical work like building models and applying machine learning, whereas Data Analysts focus on interpreting data and creating reports. Both roles require strong analytical skills, but Data Science Associates often have a deeper understanding of programming and statistical modeling.

What can I do with an associate's degree in data science?

A Data Science Associate with an associate's degree can work as a data analyst, supporting data collection, cleaning, and basic analysis using tools like Excel, SQL, and Python. They often assist in generating reports, visualizations, and insights under supervision, and may pursue certifications to advance into more specialized roles.

What are the most commonly searched types of Data Science jobs in Napa, CA?

The most popular types of Data Science jobs in Napa, CA are:

What job categories do people searching Data Science Associate jobs in Napa, CA look for?

The top searched job categories for Data Science Associate jobs in Napa, CA are:

What cities near Napa, CA are hiring for Data Science Associate jobs?

Cities near Napa, CA with the most Data Science Associate job openings:

Data Science Associate jobs near you
Infographic showing various Data Science Associate job openings in Napa, CA as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 17% Part Time, and 2% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $77,120 per year, or $37.1 per hour.

Lead Data Engineer

Qcells

San Francisco, CA • On-site

$160K - $220K/yr

Full-time

Re-posted 28 days ago

Key responsibilities

  • Lead the design, development, and optimization of scalable data pipelines supporting ingestion, transformation, and enterprise-wide data consumption.

  • Architect and implement enterprise-grade ETL/ELT frameworks using Azure Fabric or comparable cloud data platforms.

  • Collaborate with cross-functional teams to translate requirements into scalable data solutions.

Qcells rating

6.8

Company rating: 6.8 out of 10

Based on 24 frontline employees who took The Breakroom Quiz

Job description

Description
POSITON DESCRIPTION
We are seeking a Lead Data Engineer to architect, build, and lead the development of scalable, cloud-based data platforms that support enterprise analytics, operational reporting, and advanced data use cases. This role provides technical leadership in designing and optimizing ETL/ELT frameworks using Azure data services (Fabric, Data Lake, Data Factory), integrating data from ERP, CRM, and operational systems, and establishing robust data models within a modern Lakehouse architecture.
The ideal candidate brings deep SQL and Python expertise, extensive experience with distributed data platforms, and strong knowledge of data architecture, governance, and performance optimization. This individual will serve as a technical leader and mentor, partnering closely with architects, analysts, application teams, and business stakeholders to deliver reliable, scalable, and well-governed enterprise data solutions.
RESPONSIBILITIES
  • Lead the design, development, and optimization of scalable data pipelines supporting ingestion, transformation, and enterprise-wide data consumption.
  • Architect and implement enterprise-grade ETL/ELT frameworks using Azure Fabric or comparable cloud data platforms.
  • Oversee and optimize data integrations from ERP (NetSuite/SAP), CRM (Salesforce), internal systems, APIs, and third-party data sources.
  • Design and govern high-quality, scalable data models supporting analytics, reporting, operational systems, and advanced use cases.
  • Partner with Data Architects to define and implement Lakehouse patterns, Delta Lake strategies, medallion architecture, and domain-driven design principles.
  • Establish and enforce data quality frameworks, validation standards, lineage tracking, and observability practices.
  • Drive performance optimization, scalability, reliability, and cost governance across cloud environments.
  • Provide technical leadership and mentorship to data engineers; conduct design reviews and enforce engineering best practices.
  • Collaborate cross-functionally with analysts, application teams, and business stakeholders to translate requirements into scalable data solutions.
  • Lead MDM, metadata management, governance, and data standardization initiatives.
  • Oversee CI/CD automation, DevOps integration, testing frameworks, and monitoring strategies for data workflows.
  • Evaluate emerging technologies and recommend platform improvements aligned with enterprise strategy.
MINIMUM QUALIFICATIONS
  • 10+ years of experience in data engineering, data architecture, or related roles.
  • Proven experience leading large-scale data platform initiatives in cloud environments.
  • Extensive hands-on experience with Azure data services (Data Lake, Data Factory, Fabric, Synapse, or similar).
  • Advanced proficiency in SQL and Python; experience with Spark or distributed processing frameworks.
  • Deep experience designing and implementing enterprise ETL/ELT frameworks.
  • Strong expertise in data modeling (dimensional modeling, star schema, lakehouse/Delta modeling).
  • Experience integrating complex enterprise systems (ERP, CRM, operational platforms).
  • Strong understanding of data governance, metadata management, MDM, and data quality frameworks.
  • Experience with performance tuning, workload optimization, and cloud cost management.
  • Demonstrated ability to lead technical teams, conduct architecture reviews, and mentor engineers.
  • Strong problem-solving, debugging, and system design skills.
  • Travel may be required up to 5%, depending on business needs.
PREFERRED QUALIFICATIONS
  • Experience with Delta Tables, Snowflake, Synapse, or comparable cloud data platforms.
  • Experience with event-driven and streaming architectures (Kafka, Event Hub, streaming pipelines).
  • Familiarity with finance, operations, energy, or ERP-driven data domains.
  • Experience designing API-based data integrations and modern integration patterns.
  • Azure certifications (Data Engineer Associate, Solutions Architect, or equivalent).
  • Experience enabling analytics teams, data science workflows, or ML pipelines.
  • Experience implementing enterprise data security and compliance frameworks.
USE OF AI TOOLS
As a technology organization, Qcells expects team members to leverage AI models and AI-assisted tools in their daily workflows where appropriate. Candidates should be comfortable working in an AI-augmented environment and applying sound judgment when using AI-generated outputs.
During the interview process, candidates will be asked to share examples of how they have used AI tools or models in their work.
Hanwha Q CELLS America Inc. ("HQCA") is a Qcells company, one of the world's largest manufacturers and providers of solar photovoltaic (PV) products and solutions. Headquartered in Irvine, California, HQCA has been rapidly expanding its business in North America through the expansion of products and solutions, including distributed energy solutions, direct-to-homeowner solar sales and financing, and EPC services. We provide an opportunity to be part of an exciting and growing world-class global business in an interesting and expanding industry of the future.
PHYSICAL, MENTAL & ENVIRONMENTAL DEMANDS:
To comply with the Rehabilitation Act of 1973 the essential physical, mental and environmental requirements for this job are listed below. These are requirements normally expected to perform regular job duties. Incumbent must be able to successfully perform all of the functions of the job with or without reasonable accommodation.
Mobility
Standing
20% of time
Sitting
70% of time
Walking
10% of time
Strength
Pulling
up to 10 Pounds
Pushing
up to 10 Pounds
Carrying
up to 10 Pounds
Lifting
up to 10 Pounds
Dexterity (F = Frequently, O = Occasionally, N = Never)
Typing
F
Handling
F
Reaching
F
Agility (F = Frequently, O = Occasionally, N = Never)
Turning
F
Twisting
F
Bending
O
Crouching
O
Balancing
N
Climbing
N
Crawling
N
Kneeling
N
The salary range is required by the California Pay Transparency Act and may differ depending on the location of those candidates hired nationwide. Actual compensation is influenced by a wide array of factors including but not limited to, skill set, education, licenses and certifications, essential job duties and requirements, and the necessary experience relative to the job's minimum qualifications.
*This target salary range is for CA positions only and should not be interpreted as an offer of compensation.
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