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Big Data Scientist Jobs (NOW HIRING)

Job Purpose We are seeking a data scientist who is interested in helping to build and scale genome ... analysis, big data and cloud development. The successful candidate will have the opportunity to ...

Company Description SRP is a big data company located in Princeton, NJ focused on Dynamic Pricing, run by seasoned alumni from Stanford University and Wharton. Title: Senior Data Scientist for a ...

Company Description SRP is a big data company located in Princeton, NJ focused on Dynamic Pricing, run by seasoned alumni from Stanford University and Wharton. Title: Senior Data Scientist for a ...

ECS seeks a Data Scientist to support the development and integration of Big Data/Cloud Solutions. The candidate will have experience in managing, manipulating, storing and parsing data for various ...

Big Data Engineer

Los Angeles, CA · On-site

$60 - $79.50/hr

Having the dynamic ability to adapt to conventional big-data frameworks and tools with the use-cases required by the project Ability to communicate with research teams and data scientists, finding ...

Data Scientist

Boulder, CO · On-site

$130K - $160K/yr

Product Pulse is seeking a Data Scientist to help us unlock the value in our data. WHAT YOU NEED TO ... Experience with big data tools is a plus. APPLY TODAY If you're ready to make data actionable and ...

Dynamis is seeking a Data Scientist II to apply machine learning, statistical analysis, and network ... Use big data tools and proprietary data to answer mission and business questions. * Present ...

Job Title: Data Scientist Job Location: Detroit, MI (Hybrid) Job Type: Contract * Develop and ... Experience with cloud platforms (AWS preferred) and Big Data technologies. * Experience with ...

New

Dynamis is seeking a Data Scientist II to apply machine learning, statistical analysis, and network ... Use big data tools and proprietary data to answer mission and business questions. * Present ...

Dynamis is seeking a Data Scientist II to apply machine learning, statistical analysis, and network ... Use big data tools and proprietary data to answer mission and business questions. * Present ...

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Big Data Scientist information

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$46K

$165K

$243.5K

How much do big data scientist jobs pay per year?

As of Jun 15, 2026, the average yearly pay for big data scientist in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

What are Big Data Scientists?

Big Data Scientists are professionals who analyze and interpret large, complex data sets to uncover patterns, trends, and insights that help organizations make data-driven decisions. They use advanced analytics, machine learning, and statistical modeling techniques to process and extract value from massive volumes of structured and unstructured data. Their work often involves programming, data mining, and working with big data technologies such as Hadoop and Spark.

What are some common challenges Big Data Scientists face when working with large datasets, and how can they be addressed?

Big Data Scientists often encounter challenges such as handling data quality issues, ensuring data security, and managing the complexity of distributed computing environments. Large datasets frequently contain inconsistencies or missing values, requiring robust data cleaning and preprocessing techniques. Additionally, working with distributed systems like Hadoop or Spark introduces complexities around data storage, processing speed, and coordination with engineering teams. To address these challenges, it’s important to stay updated on best practices, leverage automation tools, and maintain close collaboration with data engineers and IT teams.

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

To thrive as a Big Data Scientist, you need a strong background in statistics, machine learning, programming (typically Python or R), and a relevant degree in computer science, mathematics, or a related field. Expertise with big data technologies such as Hadoop, Spark, and experience with cloud platforms and relevant certifications (like AWS Certified Data Analytics) are highly valuable. Analytical thinking, problem-solving, and effective communication are crucial soft skills for translating complex data insights to stakeholders. These capabilities are essential for extracting actionable, high-impact insights from massive datasets to drive business decisions.

What is the difference between Big Data Scientist vs Data Analyst?

AspectBig Data ScientistData Analyst
Required CredentialsAdvanced degrees in Data Science, Computer Science, or related fields; certifications like Cloudera, HortonworksBachelor's or Master's in Statistics, Data Analysis, or related fields; certifications like Microsoft Data Analyst
Work EnvironmentBig data platforms, cloud environments, programming in Python, R, ScalaExcel, SQL, visualization tools, basic scripting
Employer & Industry UsageTech companies, finance, healthcare, e-commerce handling large datasetsRetail, marketing, small to medium businesses analyzing customer data

Big Data Scientists focus on developing models and algorithms to analyze vast datasets using advanced tools and programming. Data Analysts interpret data, generate reports, and provide insights primarily through visualization and SQL queries. Both roles are essential but differ in complexity, tools, and scope of data handled.

What cities are hiring for Big Data Scientist jobs? Cities with the most Big Data Scientist job openings:

Full-time

Posted 29 days ago


Job description

Overview:
Role: Senior Data Scientist
Location: Aguanga, CA
Duration: 6 months
Digital Data Science, AI and Data Analytics MRC
Data Scientist with strong experience in Machine Learning, Programming, Data Visualization, and Big data tools.
Design data-driven solutions to improve business outcomes.
Assess and refine data sources and methodologies.
Collaborate with cross-functional teams to understand business needs.
Mentor junior data scientists and guide project execution.
Present insights in clear, actionable formats to stakeholders.