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Exploratory Data Analysis Jobs in California (NOW HIRING)

Walmart

(USA) Principal, Data Analyst

San Mateo, CA · On-site

$117K - $234K/yr

The position requires expertise in data quality management, exploratory data analysis, and effective communication of insights to influence stakeholders. You will lead initiatives that drive ...

Walmart

(USA) Principal, Data Analyst

San Jose, CA · On-site

$117K - $234K/yr

The position requires expertise in data quality management, exploratory data analysis, and effective communication of insights to influence stakeholders. You will lead initiatives that drive ...

Walmart

(USA) Principal, Data Analyst

Sunnyvale, CA · On-site

$117K - $234K/yr

The position requires expertise in data quality management, exploratory data analysis, and effective communication of insights to influence stakeholders. You will lead initiatives that drive ...

Walmart

(USA) Principal, Data Analyst

Cupertino, CA · On-site

$117K - $234K/yr

The position requires expertise in data quality management, exploratory data analysis, and effective communication of insights to influence stakeholders. You will lead initiatives that drive ...

Walmart

(USA) Principal, Data Analyst

Fremont, CA · On-site

$117K - $234K/yr

The position requires expertise in data quality management, exploratory data analysis, and effective communication of insights to influence stakeholders. You will lead initiatives that drive ...

Walmart

(USA) Principal, Data Analyst

Hayward, CA · On-site

$117K - $234K/yr

The position requires expertise in data quality management, exploratory data analysis, and effective communication of insights to influence stakeholders. You will lead initiatives that drive ...

Walmart

(USA) Principal, Data Analyst

Mountain View, CA · On-site

$117K - $234K/yr

The position requires expertise in data quality management, exploratory data analysis, and effective communication of insights to influence stakeholders. You will lead initiatives that drive ...

Walmart

(USA) Principal, Data Analyst

Milpitas, CA · On-site

$117K - $234K/yr

The position requires expertise in data quality management, exploratory data analysis, and effective communication of insights to influence stakeholders. You will lead initiatives that drive ...

Maxonic, Inc.

Data Scientist

Santa Clara, CA · On-site

Data Analysis and Visualization: Conduct exploratory data analysis (EDA) to understand data characteristics and identify patterns. Utilize data visualization techniques to communicate insights ...

Apex Informatics

Data Engineer

Pleasanton, CA · On-site

$127K - $152K/yr

... Exploratory Data Analysis (EDA) You have proven hands-on experience with cloud-based data warehousing / data lake platforms such as AWS S3, GitRepo, Lambda

Covalent Corp.

Data Scientist

Sunnyvale, CA · On-site

$110K - $190K/yr

Key Responsibilities Design and implement exploratory data analyses, proof-of-concept tools, and applied machine learning solutions to address scientific, operational, and analytical problems.

Staffingine LLC

Senior Data Scientist

Los Angeles, CA · On-site

Perform exploratory data analysis to identify patterns trends and opportunities for business improvement * Collaborate with stakeholders to define key performance indicators and success metrics

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Exploratory Data Analysis information

Is 40 too old to become a data analyst?

Age is not a barrier to becoming a data analyst, as the role values skills in data analysis, programming, and tools like Excel, SQL, and Python. Many professionals transition into data analysis later in their careers by gaining relevant certifications and experience, making age less relevant than skills and adaptability.

What are some typical day-to-day responsibilities for someone in Exploratory Data Analysis?

Professionals in Exploratory Data Analysis spend their days gathering, cleaning, and examining data sets to identify patterns, trends, and potential outliers. They use statistical and visualization tools to create reports and dashboards that help stakeholders understand the data’s implications. Collaboration with data engineers, business analysts, and management is common to ensure that the analyses address real business questions. Additionally, they often refine data collection processes and suggest improvements based on their findings, contributing to more efficient and insightful data workflows.

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

To thrive in Exploratory Data Analysis, you need a strong background in statistics, data visualization, and data manipulation with a relevant degree such as in statistics, mathematics, or computer science. Proficiency with tools like Python (pandas, matplotlib, seaborn), R, SQL, and data visualization platforms such as Tableau is highly valued, and certifications in data analytics can be beneficial. Strong problem-solving skills, attention to detail, and the ability to communicate insights clearly are essential soft skills for this role. These abilities ensure that analysts can interpret complex datasets, uncover valuable trends, and present findings to inform business decisions.

What field is the highest paid data analyst?

Data analysts working in finance, technology, and healthcare tend to have the highest salaries, especially those with expertise in machine learning, statistical analysis, and advanced tools like SQL, Python, or R. Senior roles, certifications, and experience in these industries often lead to higher compensation.

What is an exploratory data analyst?

An exploratory data analyst is a professional who examines and summarizes data sets to identify patterns, trends, and relationships. They use statistical tools and programming languages like Python or R to visualize data and support decision-making processes.

What is an Exploratory Data Analysis job?

An Exploratory Data Analysis (EDA) job involves analyzing and summarizing datasets to uncover patterns, relationships, and anomalies before applying formal modeling techniques. Professionals in this role use statistical methods and visualization tools to interpret data insights, assess data quality, and guide decision-making. EDA helps organizations understand their data better, ensuring that downstream analysis and machine learning models are built on a strong foundation.

Will AI replace data analyst?

AI tools can automate routine data analysis tasks, but data analysts are essential for interpreting complex insights, making strategic decisions, and understanding context. The role of a data analyst involves skills like critical thinking, communication, and domain knowledge that AI cannot fully replicate. Therefore, AI is more likely to augment rather than replace data analysts in the foreseeable future.
What are the most commonly searched types of Exploratory Data Analysis jobs in California? The most popular types of Exploratory Data Analysis jobs in California are:
What are popular job titles related to Exploratory Data Analysis jobs in California? For Exploratory Data Analysis jobs in California, the most frequently searched job titles are:
What job categories do people searching Exploratory Data Analysis jobs in California look for? The top searched job categories for Exploratory Data Analysis jobs in California are:
Exploratory Data Analysis jobs near you
Infographic showing various Exploratory Data Analysis job openings in California as of July 2026, with employment types broken down into 83% Full Time, 14% Part Time, and 3% Contract. Highlights an 83% Physical, 4% Hybrid, and 13% Remote job distribution.
Director, Medical Analytics and Exploratory Data Science

Director, Medical Analytics and Exploratory Data Science

Revolution Medicines

Redwood City, CA • Hybrid

Other

Posted 12 days ago

Job description

The Opportunity:

We are seeking a highly motivated and scientifically rigorous Director of Biostatistics to our Medical Analytics and Exploratory Data Science Biostatistics group. This role will provide strategic and hands-on statistical leadership for exploratory data analyses, scientific publications, real-world evidence (RWE), post-marketing research, and health economics and outcomes research (HEOR) initiatives. The successful candidate will serve as a key statistical leader and individual contributor, partnering closely with cross-functional teams to generate high-quality evidence that advances our oncology pipeline and supports medical and scientific strategy.

  • Provide statistical leadership for exploratory data analyses using existing clinical trial data, real world data studies, post-marketing research, and HEOR projects.

  • Serve as a primary statistical contact for assigned projects, working collaboratively with clinical development, medical affairs, safety, statistical programming, regulatory affairs and commercial.

  • Lead the design, analysis, and interpretation of complex statistical models, including survival analysis, machine learning, and casual inference methodologies.

  • Contribute to and implement policies, standards, and procedures to ensure consistency and quality in statistical practices.

  • Manage relationships with external partners, such as contract research organizations (CROs), ensuring adherence to timelines, budgets, and quality standards.

  • Mentor and provide technical guidance to junior statisticians, fostering scientific rigor, innovation, and professional growth.

  • Contribute to regulatory and payers/HTA agencies interactions, scientific publications, abstracts, and internal decision-making through clear and effective communication of statistical results.

Required Skills, Experience and Education:

  • Ph.D. or M.S. in Statistics/Biostatistics, a minimum of 8 years (for Ph.D.) and 12 years (for M.S.) of experience in biotech/pharma industry as a statistician.

  • Solid knowledge of statistical methodologies for oncology, including survival analysis and causal inference.

  • Hands-on experience in exploratory analysis of oncology trials.

  • Proven ability to independently lead statistical aspects of complex, cross-functional projects.

  • Strong understanding of regulatory requirements related to biostatistical activities and clinical trials.

  • Excellent verbal and written communication skills are required.

  • Excellent interpersonal and project management skills are essential.

  • Proficiency in SAS and/or R.

Preferred Skills:

  • Knowledge of RWD and health economics and outcomes research (HEOR) in oncology is a plus.

  • Familiarity with machine learning or advanced modeling approaches applied to biomedical or observational data. 

    #LI-Hybrid  #LI-SH1

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