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Data Analytics Jobs in Santa Rosa, CA (NOW HIRING)

Block

Staff Data Scientist, Pricing

Bodega Bay, CA · On-site

The Role The Data Science team at Block turns insights from our unique datasets into actions that ... Own end-to-end execution across the stack - analysis, pipeline, ETL, experimentation, and ...

Essential Oxygen

Marketing Analytics Manager

Novato, CA · Remote

$35 - $45/hr

Analyze customer behavior and performance data across Shopify, Google Analytics, Klaviyo, Amazon Seller Central, Walmart Marketplace, and other digital platforms to identify growth opportunities and ...

Essential Oxygen

Marketing Analytics Manager

Novato, CA · On-site

$35 - $45/hr

Analyze customer behavior and performance data across Shopify, Google Analytics, Klaviyo, Amazon Seller Central, Walmart Marketplace, and other digital platforms to identify growth opportunities and ...

Kavaliro

Cloud Data Engineer

Napa, CA · On-site

$115K - $151K/yr

Collaborate with technical analysts, business analysts, and line of business stakeholders to understand data requirements and implement appropriate data solutions. * Ensure data is cleansed, mapped ...

Buck Institute

AI Data Scientist-Furman lab

Novato, CA · On-site

$60K - $75K/yr

... Data Scientist / Agentic AI Engineer to join a collaborative research team focused on aging ... This role will help develop innovative AI-enabled systems for organizing, harmonizing, analyzing ...

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All JobsData Analytics JobsData Analytics Jobs in Santa Rosa, CA

Data Analytics information

See Santa Rosa, CA salary details

$26

$59

$103

How much do data analytics jobs pay per hour?

As of Sep 14, 2026, the average hourly pay for data analytics in Santa Rosa, CA is $59.86, according to ZipRecruiter salary data. Most workers in this role earn between $48.08 and $67.79 per hour, depending on experience, location, and employer.

What is data analytics?

Data analytics is the process of examining raw data to uncover trends, patterns, and insights that can inform decision-making. Professionals in this field use statistical techniques, programming, and data visualization tools to interpret complex data sets. Data analytics is applied in various industries, including business, healthcare, finance, and technology, to optimize operations, improve customer experiences, and drive strategic initiatives. The field often requires knowledge of tools like Excel, SQL, Python, and specialized analytics platforms.

How does a data analytics professional typically collaborate with other departments within an organization?

Data Analytics professionals frequently work alongside teams such as marketing, finance, operations, and product development to identify trends, solve business problems, and inform strategic decisions. Collaboration often involves gathering data requirements, interpreting findings, and presenting actionable insights in a clear and accessible manner. Effective communication and the ability to translate technical data into business terms are essential for ensuring recommendations are implemented and drive measurable impact. Regular cross-functional meetings and project-based teamwork are common, offering opportunities to learn from other disciplines and broaden one's organizational influence.

What are the key skills and qualifications needed to thrive as a data analytics professional, and why are they important?

To thrive as a Data Analytics professional, you need strong quantitative analysis skills, proficiency in statistics, and a relevant degree such as in mathematics, computer science, or a related field. Experience with technical tools like SQL, Python or R, data visualization platforms (e.g., Tableau, Power BI), and sometimes certifications like Google Data Analytics or Microsoft Certified: Data Analyst Associate are highly valuable. Critical thinking, problem-solving, and effective communication are essential soft skills for interpreting data and presenting findings to stakeholders. These skills and qualities are crucial for transforming raw data into actionable insights that drive business decision-making.

What is the difference between Data Analytics vs Data Analyst?

AspectData AnalyticsData Analyst
Role FocusAnalyzing large datasets to identify trends and insightsInterpreting data, creating reports, and supporting decision-making
Skills & CertificationsStatistical skills, data visualization, tools like SQL, Python, RData visualization, Excel, SQL, basic statistical knowledge
Work EnvironmentOften in data teams, tech companies, or consulting firmsBusiness units, marketing, finance, or operations teams
Common UsageRefers to the field or disciplineRefers to the job role or position

While both roles involve working with data, Data Analytics typically refers to the broader field or discipline focused on analyzing data to extract insights. A Data Analyst is a specific job role within that field, responsible for interpreting data, creating reports, and supporting business decisions.

Is a data analyst still a good career?

Data analysts remain in high demand across industries due to the increasing reliance on data-driven decision making. Strong skills in tools like Excel, SQL, and visualization software, along with certifications, can enhance job prospects and career growth in this field.

What jobs can a data analyst do?

A data analyst can work in roles such as business analyst, data scientist, data engineer, or reporting specialist. They analyze data to help organizations make informed decisions, often using tools like Excel, SQL, and visualization software, and may require knowledge of statistical methods and programming languages like Python or R.

What kind of jobs can you get with data analytics?

Data analytics skills can lead to roles such as data analyst, business analyst, data scientist, and data engineer. These jobs involve analyzing data to support decision-making, often requiring proficiency in tools like Excel, SQL, and Python, and may require relevant certifications or a strong understanding of statistical methods.

What are the most commonly searched types of Data Analytics jobs in Santa Rosa, CA?

The most popular types of Data Analytics jobs in Santa Rosa, CA are:

What are popular job titles related to Data Analytics jobs in Santa Rosa, CA?

For Data Analytics jobs in Santa Rosa, CA, the most frequently searched job titles are:

What job categories do people searching Data Analytics jobs in Santa Rosa, CA look for?

The top searched job categories for Data Analytics jobs in Santa Rosa, CA are:

What cities near Santa Rosa, CA are hiring for Data Analytics jobs?

Cities near Santa Rosa, CA with the most Data Analytics job openings:

Data Analytics jobs near you
Infographic showing various Data Analytics job openings in Santa Rosa, CA as of September 2026, with employment types broken down into 67% Full Time, and 33% Part Time. Highlights an 100% In-person job distribution, with an average salary of $124,501 per year, or $59.9 per hour.

Applied Data Scientist

Santa Rosa, CA • On-site

Keysight Technologies, Inc.
Electrical Equipment, Appliance, and Component Manufacturing • 10K+ employees
Learn more about Keysight Technologies, Inc.external

$117K - $196K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

This job post has expired 3 days ago. Applications are no longer accepted.

Keysight Technologies rating

8.1

Company rating: 8.1 out of 10

Based on 20 frontline employees who took The Breakroom Quiz

Job description

Overview
Keysight is at the forefront of technology innovation, delivering breakthroughs and trusted insights in electronic design, simulation, prototyping, test, manufacturing, and optimization. Our ~16,800 employees create world-class solutions in communications, 5G, automotive, energy, quantum, aerospace, defense, and semiconductor markets for customers in over 100 countries. Learn more about what we do.
Our award-winning culture embraces a bold vision of where technology can take us and a passion for tackling challenging problems with industry-first solutions. We believe that when people feel a sense of belonging, they can be more creative, innovative, and thrive at all points in their careers.
As an Applied Data Scientist, you'll operate at the intersection of data engineering, data science, and machine learning. You'll design and implement large-scale data architectures, develop robust data pipelines, and build high-quality ML models that integrate simulation and measurement data from diverse domains.
Your work will directly influence Keysight's advanced R&D initiatives, from algorithm development to AI-assisted engineering tools.
Responsibilities
  • Partner with internal engineering and data teams to identify key data sources, define feature requirements, and align data standards across organizations.
  • Design, implement, and maintain data lakes, databases, and ETL/ELT pipelines (Snowflake, Databricks, SQL, Python).
  • Integrate, clean, and align simulation, measurement, and operational data for scalable AI/ML model development.
  • Conduct exploratory data analysis, dimensionality reduction (e.g., PCA), clustering, and regression to extract insights.
  • Develop and validate ML models using tree-based methods (XGBoost, LightGBM, Random Forests) and Bayesian Optimization for tuning.
  • Apply signal processing and data augmentation techniques to improve data quality and coverage.
  • Document data lineage, feature definitions, and modeling rationale for reproducibility and transparency.
  • Communicate insights and recommendations to stakeholders, influencing data-driven decisions across R&D and product teams.

Qualifications
  • Master's or PhD in Data Science, Computer Science, Electrical Engineering, Statistics, or related field.
  • 1+ years' experience as a Data Scientist / Applied Data Scientist
  • Proven ability to build and maintain scalable data infrastructures (data lakes, schemas, pipelines).
  • Strong programming skills in Python (pandas, numpy, scikit-learn), SQL, and optionally C++.
  • Proficiency with Snowflake, Databricks, or similar big-data environments.
  • Hands-on expertise in tree-based ML techniques and statistical modeling.
  • Familiarity with Bayesian Optimization and feature engineering for time-series or signal data.
  • Ability to move fluidly between data exploration, engineering, and modeling tasks.

Desired Qualifications
  • Experience in data architecture design, schema governance, or cross-team data standards.
  • Knowledge of MLOps principles for productionizing models and maintaining pipelines.
  • Experience with metadata management and feature store design.
  • Prior exposure to environments combining simulation and real-world measurement data.

Careers Privacy Statement
Keysight Technologies Inc. is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability or any other protected categories under all applicable laws.
The level of role and salary will be based on applicable experience, education and skills; Most offers will be between the minimum and the midpoint of the Salary Range listed below.
California Pay Range: MIN $117,750- MAX $196,250
Colorado Pay Range: MIN $109,030 - MAX $181,720
Note: For other locations, pay ranges will vary by region.
US Employees may be eligible for the following benefits:
- Medical, dental and vision
- Health Savings Account
- Health Care and Dependent Care Flexible Spending Accounts
- Life, Accident, Disability insurance
- Business Travel Accident and Business Travel Health
- 401(k) Plan
- Flexible Time Off, Paid Holidays
- Paid Family Leave
- Discounts, Perks
- Tuition Reimbursement
- Adoption Assistance
- ESPP (Employee Stock Purchase Plan)

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