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Remote Data Science Jobs in Berkeley, CA (NOW HIRING)

Data Scientist

Pleasanton, CA · Remote

$75 - $80/hr

Remote Rate: $75-$80/hr on W2 Key points: Developing computer vision models that improve ... As a Delivery team, this Department uses industry leading data science and change management ...

Data Science Experts Type: Contract Compensation: $70-$100/hour Location: Remote Commitment: 40 hours/week Role Responsibilities * Guide research and engineering teams on data science methodology ...

Data Scientist

San Francisco, CA · On-site +1

$171K - $230K/yr

The Data Science team at Asana is pivotal in fulfilling our mission by fostering a data-driven approach in shaping both our product and business strategies. In your role on the Marketing Data Science ...

Tennis Data Scientist

San Francisco, CA · On-site +1

$135K - $190K/yr

Data Science is at the core of our business, so this team has true ownership and impact over developing core components of Swish's data products. This position is remote from the USA. Duties:

Our dedication to remote-first work, and strong culture of connection and global inclusion means ... You will be part of a highly visible Data Science & Analytics team that serves as the trusted ...

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Remote Data Science information

What are the key skills and qualifications needed to thrive as a Remote Data Scientist, and why are they important?

To thrive as a Remote Data Scientist, you need strong analytical skills, proficiency in statistics, and a solid background in mathematics or computer science, often supported by a relevant degree. Expertise in programming languages such as Python or R, familiarity with machine learning libraries, and experience with cloud-based data platforms are typically required. Excellent communication, self-motivation, and time management skills help you effectively collaborate and deliver results in a remote environment. These skills ensure accurate data analysis, meaningful insights, and successful teamwork despite physical distance.

How do remote data scientists typically collaborate with cross-functional teams to deliver insights?

Remote data scientists often work closely with product managers, engineers, and business analysts using digital collaboration tools such as Slack, Zoom, and project management platforms. Regular virtual meetings, code sharing via Git repositories, and clear documentation are essential to ensure alignment and transparency. While working remotely can present challenges in communication, proactive updates and scheduled syncs help foster strong teamwork and keep projects on track.

What is remote data science?

Remote data science refers to the practice of performing data analysis, modeling, and interpretation tasks from a location outside of a traditional office, such as from home or a co-working space. Remote data scientists use tools like Python, R, and SQL to analyze data, build predictive models, and communicate insights to stakeholders, all while collaborating virtually with their teams. This setup offers flexibility and can increase access to global job opportunities, but also requires strong self-motivation and communication skills to be effective.

Can a data scientist work fully remote?

Yes, many data scientists work fully remote, especially in companies that prioritize flexible work arrangements. Remote data science roles often require strong communication skills, proficiency with collaboration tools, and the ability to work independently on projects using programming languages like Python or R. However, some positions may require occasional in-person meetings or on-site presence depending on company policies.

Is 40 too late for data science?

Age is not a barrier to entering data science, and many professionals start or transition into the field later in life. Success depends on acquiring relevant skills such as programming, statistics, and machine learning, often through online courses or certifications, regardless of age.

Will AI replace data scientists?

AI is transforming the role of data scientists by automating routine tasks such as data cleaning and basic analysis, but it does not eliminate the need for human expertise in interpreting results, designing models, and making strategic decisions. Data scientists will continue to be essential for developing complex algorithms, understanding business context, and ensuring ethical use of AI tools. Skills in programming, statistical analysis, and machine learning remain critical for the profession's evolving landscape.

What Are the Qualifications to Get a Remote Data Science Job?

The qualifications for a remote data scientist depend in large part on your employer and their industry. Most employers expect remote data science professionals to have at least a bachelor’s degree in statistics, math, computer science, or a related field. Some expect postgraduate degrees in a field like data mining or machine learning or demonstrable skills in these areas. As a remote worker, you need access to relevant programs and an internet connection. You may also want to pursue certification, such as becoming a Certified Analytics Professional (CAP).

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

AspectRemote Data ScienceRemote Data Analyst
Required CredentialsDegree in Data Science, Statistics, or related field; programming skills in Python/R; knowledge of machine learningDegree in Statistics, Mathematics, or related field; proficiency in Excel, SQL, and data visualization tools
Work EnvironmentCollaborative teams, research-focused, often involves building models and algorithmsData reporting, visualization, and interpreting data trends for decision-making
Employer & Industry UsageTech companies, finance, healthcare, e-commerceMarketing agencies, retail, finance, healthcare

Remote Data Science involves developing predictive models and advanced analytics, requiring programming and machine learning skills. Remote Data Analysts focus on interpreting data, creating reports, and visualizations. While both roles analyze data remotely, Data Scientists typically handle more complex modeling tasks, whereas Data Analysts focus on data interpretation and reporting.

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 results come from 20% of the efforts or features. Data scientists often use this concept to focus on the most impactful variables, optimize models, and prioritize tasks for efficiency.
What are the most commonly searched types of Data Science jobs in Berkeley, CA? The most popular types of Data Science jobs in Berkeley, CA are:
What are popular job titles related to Remote Data Science jobs in Berkeley, CA? For Remote Data Science jobs in Berkeley, CA, the most frequently searched job titles are:
What job categories do people searching Remote Data Science jobs in Berkeley, CA look for? The top searched job categories for Remote Data Science jobs in Berkeley, CA are:
What cities near Berkeley, CA are hiring for Remote Data Science jobs? Cities near Berkeley, CA with the most Remote Data Science job openings:
Infographic showing various Remote Data Science job openings in Berkeley, CA as of June 2026, with employment types broken down into 2% As Needed, 69% Full Time, 26% Part Time, and 3% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution.
Data Science

Full-time

Posted 23 days ago


Job description

Adidev Technologies Inc 

www.adidevtechnologies.com

URGENT HIRE - HIRING PROCESS - 24-48 HOURS!

Adidev Technologies is seeking 1-2 yrs of relevant experience in Data Science. A project can last anywhere from 6 months to 18 months. Salary varies depending on experience, and we are in search of candidates looking to start as soon as possible. Excellent written and oral communication are required as is the ability to work well in a team environment.

If you are looking for a new challenge and are ready to make an impact on a growing team, then this will be a perfect fit. As a Data Scientist/Data Science Specialist for Adidev Technologies Inc., you will be enhancing and debugging large-scale applications for one of our well-known clients.

Adidev Technologies is a growing software consulting company that is constantly expanding. As we are working with renowned clients and ready to take on new ones, we are seeking brilliant software engineers. Not only do we offer a great team to work with, but we also offer you an opportunity to make an immediate impact and get rewarded accordingly

 

Job Description

  • Demonstrated experience using machine learning, deep learning, statistical methodology, and simulation/optimization modeling in geospatial, network topography, recommendation systems, environmental systems, and/or agronomic problems.
  • Strong foundation in Python programming in a cloud environment.
  • Strong quantitative abilities, distinctive problem-solving, and excellent analysis skills
  • Expertise in data wrangling using SQL,
  • Practical knowledge and experience with cloud-computing systems and platforms, including the routine deployment of pipelines through Kubernetes
  • Fluency in querying/extracting/aggregating data via SQL scripting.
  • Extract, load and transform data (ETL) from structured and unstructured sources
  • Apply Natural Language Processing and Computer Vision to solve business use cases,
  • Strong skills in scientific data analyses, modeling, visualization and communication of results.
  • Knowledge of Python libraries (NumPy, Pandas, SciKit-Learn, TensorFlow, PyTorch), Spacy, MongoDB, PostgreSQL, Flask, streamlet and a good knowledge of data pipelines construction
  • Ph.D., M.S. or B.S. in Computer Science, Computational Physics, Operations Research, Geospatial Sciences, Remote Sensing Science, Environmental Sciences, Computational Astronomy or related scientific discipline


Must  have 

  • Understanding of various machine learning algorithms (e.g. SVM, Random Forests, Gradient Boosting, Log-Log regression, XGBoost, Lasso, Ridge, Clustering techniques, Neural Networks and others)
  • Regression (e.g. ? Linear/Logistic/MNL/Mixed Effects/Regularization)
  • Classification (K-means, Hierarchical, Latent Class, DBScan, SVM)
  • Dimension Reduction techniques (Principal Component analysis, Singular Value Decomposition etc.)
  • Optimization (Linear programming, Stochastic Gradient Descent, Genetic Algorithm etc.)
  • Experience with neural network approaches to text classification CNN, RNN, LSTM,Keras
  • Machine Learning algorithms? Neural Networks, Naïve Bayes, Bagging & Boosting, Random Forest
  • Distributed computing tools and cloud technology (AWS)

QUALIFICATIONS

  • Degree in Data Science, Computer Science, Engineering, Math, or Statistics preferred
  • At least 2 yrs of relevant experience in Data Science


SKILLS

  • SQL, statistical modeling, Feature engineering, Data visualization, Deploying models to production, Python programming, AWS, Domains(Healthcare/ Manufacturing/ Marketing/ Financial/ Telecommunication), powerbi/tableau, data warehouse

Benefits

  • Competitive Salary

  • Paid Relocation

  • Remote Support

  • Guaranteed Regular Salary Reviews

  • Job Type: W2 or Contract 1099 (full-time - 40 hours)

Employment Type: FULL_TIME