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Remote Analytics Engineer Jobs in Berkeley, CA (NOW HIRING)

Swish Analytics

NFL Data Scientist

San Francisco, CA · On-site +1

$140K/yr

... analytics data products. We believe that oddsmaking is a challenge rooted in engineering ... This position is remote from the USA. Duties: * Ideate, develop and improve machine learning and ...

Swish Analytics

Soccer Data Scientist

San Francisco, CA · On-site +1

$130K/yr

... analytics data products. We believe that oddsmaking is a challenge rooted in engineering ... This position is remote from the USA. Duties: * Ideate, develop and improve machine learning and ...

Everglade Works

Software Engineer

San Francisco, CA · Remote

$60 - $80/hr

Remote Software Engineer (USA Only) | $60 - $80 per hour Are you a software engineer who thrives in ... in a remote environment. * Excellent problem-solving skills and a strong analytical mindset.

Rodan and Fields, LLC

Manager of Analytics

San Ramon, CA · On-site +1

US (Hybrid/Remote as applicable) Role Overview Rodan + Fields is seeking a highly skilled Manager ... Partner with analytics and data engineering resources to automate datasets, reporting layers, and ...

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Showing results 21-40

All JobsAnalytics Engineer JobsRemote Analytics Engineer JobsRemote Analytics Engineer Jobs in Berkeley, CA

Remote Analytics Engineer information

See Berkeley, CA salary details

$55.7K

$114.1K

$165.9K

How much do remote analytics engineer jobs pay per year?

As of Aug 6, 2026, the average yearly pay for remote analytics engineer in Berkeley, CA is $114,092.00, according to ZipRecruiter salary data. Most workers in this role earn between $85,700.00 and $144,500.00 per year, depending on experience, location, and employer.

What are the main challenges faced by remote analytics engineers, and how are they overcome?

Remote Analytics Engineers often encounter challenges such as coordinating across different time zones, maintaining clear communication with team members, and managing large datasets securely from a distance. These are typically addressed by leveraging collaboration tools (like Slack, Jira, or Zoom), following best practices in data security, and setting consistent check-in routines with the team. Additionally, remote engineers often use robust documentation and automated workflows to ensure data quality and project transparency. Building strong relationships and staying proactive in communication helps pave the way for successful collaboration and project delivery.

What is a remote analytics engineer?

A Remote Analytics Engineer is responsible for designing, building, and maintaining the data infrastructure that enables data-driven decision-making. They work with data pipelines, ETL processes, and data warehouses to ensure accurate and efficient data flow. This role typically requires expertise in SQL, Python, and data modeling, as well as experience with cloud platforms and analytics tools. Since the position is remote, strong communication and collaboration skills are essential for working with distributed teams.

What are the key skills and qualifications needed to thrive as a remote analytics engineer?

To thrive as a Remote Analytics Engineer, you should have a strong background in data analysis, data engineering, and statistical modeling, usually supported by a degree in computer science, statistics, or a related field. Expertise in tools like SQL, Python, R, cloud platforms (such as AWS or Google Cloud), and experience with data visualization tools or certifications (e.g., Google Data Analytics) are typically required. Excellent communication, problem-solving abilities, and self-motivation are vital soft skills for effective remote collaboration and delivering analytical insights. These competencies ensure you can manage complex data pipelines, work seamlessly with distributed teams, and provide actionable results that support business decisions.

Can you work remotely in data analytics?

Remote analytics engineers can work from anywhere with a reliable internet connection, as many data analysis tasks involve using cloud-based tools and programming languages like Python or SQL. Employers increasingly offer remote positions, especially for roles that focus on data modeling, visualization, and reporting, often requiring strong communication skills and familiarity with collaboration platforms.
What are popular job titles related to Remote Analytics Engineer jobs in Berkeley, CA? For Remote Analytics Engineer jobs in Berkeley, CA, the most frequently searched job titles are:
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What cities near Berkeley, CA are hiring for Remote Analytics Engineer jobs? Cities near Berkeley, CA with the most Remote Analytics Engineer job openings:
Remote Analytics Engineer jobs near you
Infographic showing various Remote Analytics Engineer job openings in Berkeley, CA as of August 2026, with employment types broken down into 92% Full Time, 2% Part Time, and 6% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $114,092 per year, or $54.9 per hour.

Machine Learning Engineer (Remote)

Astrix Inc

South San Francisco, CA • On-site, Remote

$55 - $73/hr

Full-time

Re-posted 9 days ago

Job description

Our client is a leader in healthcare innovation, seamlessly integrating pharmaceutical development, diagnostic solutions, and advanced technology and data capabilities.
Title: Machine Learning Engineer (Contract)
Pay rate: $55-73/hr+ (Depends on experience)
Location: Remote in the US or Canada, or onsite in SSF. Must be available during PST hours.
Duration: Through Dec. 2026 (Likely to get extended)
Overview:
Seeking a Machine Learning Bioinformatics Engineer to develop and deploy advanced ML solutions supporting pharmaceutical R&D. This role focuses on analyzing large-scale, multimodal clinicogenomic datasets (genomic, transcriptomic, clinical, and real-world data) to drive insights into disease biology, patient stratification, and treatment response. Ideal candidates are strong in both machine learning and bioinformatics, with a passion for translating complex data into impactful discoveries.
Key Responsibilities:
  • Build and deploy scalable, production-ready machine learning models
  • Process and analyze genomic and transcriptomic data using bioinformatics pipelines
  • Prepare high-quality, normalized biological datasets for downstream analysis
  • Train large-scale models using frameworks like PyTorch Lightning and Hugging Face
  • Develop cloud-based ML solutions (AWS/GCP) with a focus on scalability and reproducibility
  • Collaborate with cross-functional teams to uncover biomarkers and therapeutic targets
  • Provide technical input and guidance on ML system design and implementation

Qualifications:
  • PhD with 0-2 years of relevant work experience, or MS with 3-5 years of relevant work experience, or BS with 4-7 years of relevant work experience.
  • Proficient programming skills: Strong Python programming skills with extensive experience in ML and data libraries (e.g., NumPy, pandas, PyTorch).
  • Deep ML expertise: Excellent knowledge of modern machine learning methods and development best practices, including training strategies, model validation, performance visualization, and experimental design.
  • Deep bioinformatic expertise: Proficient knowledge of bioinformatic processing pipelines for genomic and transcriptomic variables.
  • Strong knowledge of computational oncology, cancer genomics and analysis of clinicogenomics datasets.
  • Must be authorized to work in the United States

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