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Data Analyst Data Science Jobs in California (NOW HIRING)

psudo

As a data analyst, you will be responsible for compiling actionable insights from data and ... Science), preferably with work experience of over 2-3 years (open to talk to freshers as well)

Excelhire

Data Analyst

Los Angeles, CA

$32/hr

Bachelor's degree in Data Science, Statistics, Computer Science, or related field * 1-3 years of experience in data analysis (preferred) * Strong knowledge of Excel, SQL, and data visualization tools ...

Tatari

Data Science Analyst

San Francisco, CA

$70K - $85K/yr

We're looking for a Data Science Analyst to join the Data Science team. In this role, you will work in a fast-paced environment with diverse data sets and technologies to build production quality ...

Tatari

Data Science Analyst

San Francisco, CA · On-site

$70K - $85K/yr

We're looking for a Data Science Analyst to join the Data Science team. In this role, you will work in a fast-paced environment with diverse data sets and technologies to build production quality ...

Tatari

Data Science Analyst

Los Angeles, CA · On-site

$70K - $85K/yr

We're looking for a Data Science Analyst to join the Data Science team. In this role, you will work in a fast-paced environment with diverse data sets and technologies to build production quality ...

AEG Worldwide

LA Kings - Sr. Data Analyst

El Segundo, CA · On-site

$91K - $115K/yr

Manage the end-to-end data science lifecycle from model design, development, deployment, maintenance, and model updates. * Provide expertise, analysis, and guidance for promotional campaigns ...

Tatari

Data Science Analyst

Los Angeles, CA

$70K - $85K/yr

We're looking for a Data Science Analyst to join the Data Science team. In this role, you will work in a fast-paced environment with diverse data sets and technologies to build production quality ...

AEG

LA Kings - Sr. Data Analyst

El Segundo, CA · On-site

$91K - $115K/yr

Manage the end-to-end data science lifecycle from model design, development, deployment, maintenance, and model updates. * Provide expertise, analysis, and guidance for promotional campaigns ...

AEG Worldwide

LA Kings - Sr. Data Analyst

El Segundo, CA · On-site

$91K - $115K/yr

Manage the end-to-end data science lifecycle from model design, development, deployment, maintenance, and model updates. * Provide expertise, analysis, and guidance for promotional campaigns ...

Swish Analytics

Sports Data Analyst

San Francisco, CA · On-site +1

Company Description Swish Analytics is a sports analytics, betting and fantasy startup building the ... Work closely with Data Scientists and Engineers to diagnose and treat data pipeline integrity ...

Adidev Technologies Inc

Data Science

San Francisco, CA · Remote

Strong skills in scientific data analyses, modeling, visualization and communication of results. * Knowledge of Python libraries (NumPy, Pandas, SciKit-Learn, TensorFlow, PyTorch), Spacy, MongoDB ...

Adidev Technologies Inc

Data Science

San Francisco, CA · On-site

Strong skills in scientific data analyses, modeling, visualization and communication of results. * Knowledge of Python libraries (NumPy, Pandas, SciKit-Learn, TensorFlow, PyTorch), Spacy, MongoDB ...

Hayden AI

Data Analyst

San Francisco, CA · On-site

$123K - $160K/yr

This is a great opportunity for someone who wants to deliver a big impact: you'll be supporting the Data Science team and operate at the intersection of Data Engineering, Analytics and Data Science.

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All JobsData Analyst Data Science JobsData Analyst Data Science Jobs in California

Data Analyst Data Science information

Is 40 too late for data science?

Data analysts and data scientists can start their careers at any age, including 40 or older. Success in data science depends on acquiring relevant skills such as programming, statistics, and tools like Python or R, which can be learned at any stage of life. Many professionals transition into data roles later in their careers with dedication and continuous learning.

How do Data Analysts in Data Science typically collaborate with other departments or teams?

Data Analysts in Data Science frequently work cross-functionally, partnering with teams such as engineering, product management, marketing, and business intelligence. They translate complex data findings into actionable insights and tailor their communication to both technical and non-technical stakeholders. Regular collaboration may involve participating in meetings to understand business needs, designing dashboards for different teams, and providing data-driven recommendations to support company objectives. This collaborative environment not only enhances project outcomes but also fosters continuous learning and professional growth.

What is the 80 20 rule in data science?

In data science, the 80/20 rule, also known as the Pareto principle, suggests that roughly 80% of the results come from 20% of the efforts or data. Data analysts often use this concept to focus on the most impactful variables or features during analysis and modeling to improve efficiency and accuracy.

What does a Data Analyst in Data Science do?

A Data Analyst in Data Science collects, processes, and analyzes large sets of data to help organizations make informed decisions. They use statistical techniques and data visualization tools to identify trends, patterns, and insights from data. Their responsibilities often include cleaning data, creating reports, and communicating findings to stakeholders. Data Analysts play a key role in helping businesses optimize operations, understand customer behavior, and solve complex problems using data-driven approaches.

Can data science work as a data analyst?

Data science and data analysis are related fields, but they have different focuses. Data scientists often develop models and algorithms using programming languages like Python or R, while data analysts primarily interpret data, generate reports, and use tools like Excel or SQL. Skills in statistical analysis, data visualization, and understanding business needs are essential for both roles, and some professionals transition between them based on experience and training.

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

AspectData Analyst Data ScienceData Engineer
Required SkillsStatistics, programming (Python, R), data visualizationDatabase systems, ETL pipelines, programming (Python, Java)
Work EnvironmentAnalyzing data, building models, reportingBuilding and maintaining data infrastructure
CertificationsData Science certifications, SQL, PythonCloud certifications, database management
Industry UsageBusiness analysis, predictive modelingData infrastructure, big data systems

Data Analyst Data Science focuses on analyzing data and creating models to inform decisions, while Data Engineers build the systems that collect, store, and process data. Both roles require programming skills and often overlap in tools like Python and SQL, but their core responsibilities differ significantly.

What are the key skills and qualifications needed to thrive as a Data Analyst in Data Science, and why are they important?

To thrive as a Data Analyst in Data Science, you need strong analytical skills, proficiency in statistics, and a relevant degree such as in mathematics, computer science, or a related field. Familiarity with tools like SQL, Python or R, and data visualization platforms such as Tableau or Power BI, along with industry-recognized certifications, is highly valued. Attention to detail, problem-solving abilities, and effective communication skills help you interpret data insights and convey findings to stakeholders. These skills are crucial for transforming raw data into actionable intelligence that drives strategic business decisions.

Is AI replacing data analysts?

AI is transforming the role of data analysts by automating routine tasks such as data cleaning and basic analysis, allowing analysts to focus on more complex insights and strategic decision-making. While AI tools can augment their work, human expertise remains essential for interpreting results, understanding context, and communicating findings effectively. Data analysts who develop skills in machine learning, programming, and data visualization will continue to be valuable in the evolving data science environment.
What are popular job titles related to Data Analyst Data Science jobs in California? For Data Analyst Data Science jobs in California, the most frequently searched job titles are:
What job categories do people searching Data Analyst Data Science jobs in California look for? The top searched job categories for Data Analyst Data Science jobs in California are:
What cities in California are hiring for Data Analyst Data Science jobs? Cities in California with the most Data Analyst Data Science job openings:
Data Analyst Data Science jobs near you
Data Analyst / Data Scientist

Data Analyst / Data Scientist

psudo

On-site, Remote

Full-time

Posted 11 days ago

Job description

Other locations: Canada, London, India & Australia.


Remote: OK


Job role:

As a data analyst, you will be responsible for compiling actionable insights from data and assisting program, sales and marketing managers build data-driven processes. Your role will involve driving initiatives to optimize for operational excellence and revenue.

Responsibilities:

  • Ensure that data flows smoothly from source to destination so that it can be processed
  • Utilize strong database skills to work with large, complex data sets to extract insights
  • Filter and cleanse unstructured (or ambiguous) data into usable data sets that can be analyzed to extract insights and improve business processes
  • Identify new internal and external data sources to support analytics initiatives and work with appropriate partners to absorb the data into new or existing data infrastructure
  • Build tools for automating repetitive asks so that bandwidth can be freed for analytics
  • Collaborate with program managers and business analysts  to help them come up with actionable, high-impact insights across product lines and functions
  • Work closely with top management to prioritize information and analytic needs

Requirements:

  • Bachelors or Masters in a quantitative field (such as Engineering, Statistics, Math, Economics, or Computer Science with Modeling/Data Science), preferably with work experience of over 2-3 years (open to talk to freshers as well).
  • Ability to program in any high level language is required. Familiarity with R and statistical packages are preferred.
  • Proven problem solving and debugging skills.
  • Familiar with database technologies and tools (SQL/R/SAS/JMP etc.), data warehousing, transformation and processing. Work experience with real data for customer insights, business and market analysis will be advantageous.
  • Experience with text analytics, data mining and social media analytics.
  • Statistical knowledge in standard techniques: Logistic Regression, Classification models, Cluster Analysis, Neural Networks, Random Forests, Ensembles, etc.
Employment Type: FULL_TIME

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