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Volunteer Computer Data Scientist Jobs in California

Apple

Data Scientist

Cupertino, CA · On-site

Minimum Qualifications MS/PhD in Computer Science, Statistics, Physics, Operations Research, or similar quantitative domain 3+ years experience with data analysis at web scale or relevant work ...

Vianai Systems

Data Scientist

Palo Alto, CA · On-site +1

$115K - $180K/yr

Our ideal Data Scientist is hands-on, collaborative, self-motivated, and innovative. She or he ... M.S. in Computer Science, Applied Mathematics, Statistics or related field. * Proven track record ...

NextDeavor Inc.

Data Scientist

San Francisco, CA

$90.14 - $112.68/hr

Data Scientist Full-time San Francisco, CA, US You'll be joining Adobe on a contract opportunity ... Bachelor's degree in a quantitative field (Computer Science, Math/Statistics, Economics, Physics ...

Vianai Systems

Data Scientist

Palo Alto, CA · On-site +1

$115K - $180K/yr

Our ideal Data Scientist is hands-on, collaborative, self-motivated, and innovative. She or he ... M.S. in Computer Science, Applied Mathematics, Statistics or related field. * Proven track record ...

Teichert

Data Scientist

Sacramento, CA · On-site

Master's degree or PhD in Data Science, Statistics, Computer Science, Applied Mathematics, Engineering, or a related quantitative field. Experience and Industry Expertise: * Minimum 5 years of hands ...

Careers at Teichert

Data Scientist

Sacramento, CA

Master's degree or PhD in Data Science, Statistics, Computer Science, Applied Mathematics, Engineering, or a related quantitative field. Experience and Industry Expertise: * Minimum 5 years of hands ...

New

Reddit

Senior Data Scientist

San Francisco, CA · On-site +1

$229K - $267K/yr

... Research, Economics, Computer Science, Engineering (any field), or a related quantitative ... Flexible Vacation & Paid Volunteer Time Off * Generous Paid Parental Leave Submit a resume with ...

Cypress HCM

Data Scientist

San Jose, CA · On-site

$105.63/hr

Bachelor's degree in computer science, statistics, physics or a related field is required. A Master's degree in this field is preferred. * 3-5+ years of direct experience as a Data Scientist * Deep ...

Apple

Data Scientist, AIML Data Scientist

Cupertino, CA · On-site

Minimum Qualifications Bachelors degree in Computer Science, Statistics, Mathematics, Engineering, Economics or related field. 4+ years of experience in data science with proven skills in developing ...

BeeGenius

Data Scientist

Los Angeles, CA · On-site

D. in Computer Science, Statistics, or a related field • Proficiency in programming languages ... of data visualization tools and techniques • Excellent communication and presentation skills ...

BeeGenius

Data Scientist

Los Angeles, CA · On-site

D. in Computer Science, Statistics, or a related field • Proficiency in programming languages ... of data visualization tools and techniques • Excellent communication and presentation skills ...

(unknown company)

Data Scientist

Sunnyvale, CA

Data Scientist Location: Sunnyvale Duration: 6 Months + Minimum Qualifications - PhD in Computer Science, Statistics or related field; OR a Master's degree or equivalent in Computer Science ...

VSolvit, LLC.

DATA SCIENTIST II

Norco, CA · On-site

$115 - $130/hr

Bachelor's degree in Computer Science, Data Science, Mathematics, Statistics, Engineering, or ... voluntary benefits. Our goal is to grow together and enjoy the work that we do as a team. VSolvit ...

(unknown company)

Data Scientist

Sunnyvale, CA · On-site

Data Scientist Location: Sunnyvale Duration: 6 Months + Minimum Qualifications - PhD in Computer Science, Statistics or related field; OR a Master's degree or equivalent in Computer Science ...

Fanatics Collectibles

Data Scientist

Los Angeles, CA

Bachelor's degree in Statistics, Mathematics, Computer Science, Data Science, or another quantitative field, or equivalent practical experience. * 1-3 years of experience in data science, analytics ...

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Showing results 21-40

All JobsVolunteer Computer Data Scientist JobsVolunteer Computer Data Scientist Jobs in California

Volunteer Computer Data Scientist information

What is the difference between Volunteer Computer Data Scientist vs Volunteer Data Analyst?

AspectVolunteer Computer Data ScientistVolunteer Data Analyst
Required CredentialsBasic programming skills, knowledge of data science toolsData analysis skills, proficiency in Excel, SQL
Work EnvironmentCollaborative projects, nonprofit or research settingsData interpretation, reporting in nonprofit or community projects
Employer & Industry UsageResearch institutions, nonprofits, tech startupsNonprofits, community organizations, small businesses

Volunteer Computer Data Scientists and Volunteer Data Analysts often share similar skills like data handling and analysis. However, data scientists typically focus on building models and advanced analytics, while data analysts concentrate on interpreting data and creating reports. Both roles are vital in nonprofit and research settings, but data scientists usually require more technical expertise in programming and machine learning.

Can you get a volunteer computer data scientist job with no experience?

Volunteer computer data scientist roles often accept candidates with limited or no professional experience, especially if they have relevant skills such as programming, data analysis, or familiarity with tools like Python or R. Building a portfolio through personal projects, online courses, or certifications can improve chances of securing such volunteer positions. However, some roles may require basic understanding of data concepts or prior exposure to data science environments.

What are the most commonly searched types of Computer Data Scientist jobs in California?

The most popular types of Computer Data Scientist jobs in California are:

What cities in California are hiring for Volunteer Computer Data Scientist jobs?

Cities in California with the most Volunteer Computer Data Scientist job openings:

Volunteer Computer Data Scientist jobs near you

Data Scientist

Avani Technology Solutions, Inc.

San Francisco, CA • On-site

Full-time

Re-posted 27 days ago

Job description

Role: Data Scientist
Location: San Francisco, CA
Duration: 6+ Months
Team Overview:
The Digital Catalyst Team is a new enterprise team that is responsible for working collaboratively with the lines of business to implement consumer grade mobile and analytical solutions across various user groups (e.g., field users, office workers, etc.). This includes, but is not limited to:
  • Deploying best-in-class / rapid delivery capability for mobile solutions.
  • Simplifying, improving, and standardizing business work management processes for mobile needs.
  • Delivering high value analytics across all Lines of Businesses.
  • Rapid delivery of web applications.

Digital Catalyst consists of a staff of highly skilled professionals working together to produce mobile solutions following an agile methodology and design thinking. We are a "start-up" department within IT and building driven and creative mobile development team. We take the time to understand our partners' needs and translate those into solutions that delight our users. Our goal is to deliver products with intuitive user experience that will improve employees' and customer's safety, productivity and overall well-being.
Position Summary:
We are seeking an experienced Data Scientist in the Digital Catalyst Team who will provide strong execution and delivery of data science. Working as a part of the product team, this Data Scientist will translate business needs into advanced analytics and machine learning models. The successful candidate will be responsible for model selection and identification of appropriate training data sets; building, training, and evaluating models; and delivering results to the business on a regular cadence. This role is part of a fully Agile Scrum team, so the data scientist will work alongside a product owner, technical lead, and team of developers and data engineers to support delivery of high-value analytics and software products.
Position Responsibilities:
  • Leads development of high complexity models and training sets
  • Provides hands-on execution and implementation of data science models
  • Translates business analysis needs into well-defined data science problems, and selecting appropriate models and algorithms and communicates model evaluation and implications of results back to stakeholders
  • Recognizes and prioritizes the most important work related to data science models to achieve highest operational impact for analytics in the business
  • Balances tradeoffs among analytics value, model development methods and design and technologies used to implement data science models with a bias toward action
  • Performs collaborative work on data science problems and mentor junior data scientists
  • Creates shared process models, business objects, activity diagrams and process documentation to effectively articulate multiple views of the business solutions that support technical architecture.
  • Manages development of quantitative models and tools.
  • Collaborates with leaders, other LOBs, and business partners to work on issues, projects or activities.
  • Develops new or revises complex models to predict business demand trends, and volume and expenditures forecasts capacity analysis, and various other metrics to identify potential opportunities.
  • Assesses business implications associated with modeling assumptions, inputs, methodologies, technical implementation, analytic procedures and processes, and advanced data analysis.
  • Partners with leaders to drive high performance in their lines of business.
  • Develop deep understanding of business drivers and financial levers to provide strategic decision support.
  • Oversees resolution of complex projects and programs.
  • Develops and maintains up-to-date detailed project schedules and work plans.
  • Performs analysis on complex data models requiring customized reports and data and presents recommendations.

Minimum Education/Skills:
  • Bachelor's Degree in Econometrics, Economics, Engineering, Mathematics, Applied Sciences, Statistics or job-related discipline or equivalent experience
  • Job-related experience, 8 years, OR Master's Degree and job-related experience, 6 years, OR Doctorate Degree and job-related experience, 3 years
  • Experience in data modeling, 5yrs

Desired Education / Skills:
  • PhD in engineering or a related field (computer science, natural sciences, mathematics)
  • Experience with Python, R, Scala, SQL
  • Experience developing solutions with Pandas/Scikit-learn, Spark or comparable technologies
  • Experience data science notebooks (Jupyter, Zeppelin or other)
  • Experience with AWS, Azure, cloud computing technologies
  • Scrum team experience
  • Energy industry experience
  • Experience designing efficient data science workflows and database architecture for data science purposes
  • Experience with forecasting, Bayesian networks, and graph analytics
  • Strong statistics experience
  • Experience with software development methodologies and software engineering principles
  • Knowledge of program management theories, concepts, methods, best practices, and techniques as needed to perform at the job level
  • Knowledge of relevant programming languages - for example Visual Basic, Ladder Logic,
  • Programmable Logic Controller, C, SharePoint, HTML, Java, Adobe - as needed to perform at the job level
  • Competency in knowing the most effective and efficient processes to get things done, with a focus on continuous improvement
  • Knowledge of principles, techniques, and procedures used for production and design of technology based equipment and systems as needed to perform at the job level
  • Knowledge of statistical theories, concepts, methods, best practices, and analyses as needed to perform at the job level
  • Ability to develop reports, models, and simulations as needed to perform at the job level
  • Competency in developing and delivering multi-mode communications that convey a clear
  • understanding of the unique needs of different audiences
  • Knowledge of data model design philosophies and methodologies for data warehouse and OLTP systems

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