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Big Data Scientist Jobs (NOW HIRING)

Jobsbridge

Big Data Scientist

San Francisco, CA · On-site

Statistical analysis expertise Data modeling, including reverse and forward engineering Database Design: RDMS along with Data Warehouse, Data Mart and Data Mining Data Modeling Tools: IBM Rational ...

Smart Synergies

Big Data Engineer

Reston, VA · On-site

$58 - $76.75/hr

Frequent interaction with data scientists, project managers, IT teams, and business stakeholders. Key Responsibilities * Design and implement big data architectures, including ingestion, processing ...

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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 Sep 10, 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 is a big data scientist?

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 the key skills and qualifications needed to thrive as a big data scientist?

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 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 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.

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Big Data Scientist jobs near you
Infographic showing various Big Data Scientist job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $165,018 per year, or $79.3 per hour.

Data Scientist/Big Data Architect

Irving, TX • On-site

Apex Informatics
IT Services • 1 - 10 employees
Learn more about Apex Informaticsexternal

Contractor

This job post has expired today. Applications are no longer accepted.

Job description

Job Title- Data Scientist/Big Data Architect
Location- Irving Texas 75062 (Hybrid), (3 days onsite/2 WFH)
Duration- 09 Months Contract
Job Description:
Required Qualifications:
• 5+ years of Technology Infrastructure Engineering and Solutions experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
• 5+ years of experience troubleshooting environments across the entire architecture (i.e. applications to infrastructure)
• 4+ years of Linux experience
• 2+ years of experience with Artificial Intelligence, Business Intelligence or Machine Learning
• Knowledge and understanding of Machine Learning, Deep Learning, Linear Regression, Models (Tensor Flow), Business Intelligence and Analytics
• Experience in Artificial Intelligence, Natural Language Processing, Machine Learning, Distributed Computing, Chatbot, and Virtual Assistant
• Experience with Big Data or Hadoop tools such as Spark, Hive, Kafka and MapR
• Ability to lead projects/initiatives with high risk and complexity

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