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Data Mining Scientist Jobs (NOW HIRING)

As an Advanced Data Scientist, you will be responsible for data engineering, leveraging closed and ... Some exposure with application of data mining algorithms and statistical modeling techniques such ...

Overview BigBear.ai is seeking a Senior Data Scientist to conduct data analytics, data engineering, data mining, exploratory analysis, predictive analysis, and statistical analysis using scientific ...

Doctorate or Masters + 2 years of data science, business, statistics, data mining, applied mathematics, business analytics, engineering, computer science or related field experience. * Bachelors + 4 ...

Overview BigBear.ai is seeking a Senior Data Scientist to conduct data analytics, data engineering, data mining, exploratory analysis, predictive analysis, and statistical analysis using scientific ...

Data Scientist

Dallas, TX · On-site

$125K/yr

Data Scientist Job Location: 8115 Preston Road, Suite 400, Dallas, TX 75204 Rate of Pay: $125,000 ... Perform data analysis, mining, and statistical modeling using data engineering best practices.

Qualifications for Data Scientist Strong problem solving skills with an emphasis on product ... GLM Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc ...

Data Mining, Data Visualization, Foundations of Analytics, Database Management, Web Analytics ... Enablement Science Deliverables Resource will deliver a Large Language Model (LLM) solution to ...

Conduct data analytics, data engineering, data mining, exploratory analysis, predictive analysis, and statistical analysis to uncover insights and enable data-driven decisions. Use scientific methods ...

Conduct data analytics, data engineering, data mining, exploratory analysis, predictive analysis, and statistical analysis to uncover insights and enable data-driven decisions. Use scientific methods ...

Data Scientist

Dallas, TX · On-site

$125K/yr

Data Scientist Job Location: 8115 Preston Road, Suite 400, Dallas, TX 75204 Rate of Pay: $125,000 ... Perform data analysis, mining, and statistical modeling using data engineering best practices.

Data Scientist - Mid

Reston, VA · On-site

$140K - $155K/yr

Conduct data analytics, data mining, exploratory analysis, predictive analysis, and statistical analysis, and uses scientific techniques to correlate data into graphical, written, visual and verbal ...

New

Data Scientist LOCATION: San Bruno, CA Duration: 6 to 12+ Months Description: Role Specific ... Design and build new data set processes for modeling, data mining, and production purposes.

Data Scientist 2

Annapolis, MD · On-site

$122K - $168K/yr

The focus of this position will be on rapid prototyping and data mining. The Level 2 Data Scientist shall possess the following capabilities: * Foundations: (Mathematical, Computational, Statistical)

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Data Mining Scientist information

See salary details

$37.5K

$122.7K

$196.5K

How much do data mining scientist jobs pay per year?

As of Jul 3, 2026, the average yearly pay for data mining scientist in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

Is a data scientist in high demand?

Data scientists are in high demand across many industries due to the increasing reliance on data-driven decision making. The role often requires skills in programming, statistical analysis, and machine learning, and job growth is expected to remain strong in the coming years.

Is 30 too late for data science?

Data Mining Scientists and other data science roles often value skills and experience over age. Many professionals transition into data science in their 30s or later by acquiring relevant skills such as programming, statistics, and machine learning, often through online courses or certifications. Age is generally not a barrier if you develop the necessary technical expertise and practical experience.

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

AspectData Mining ScientistData Analyst
Required CredentialsBachelor's or Master's in Data Science, Computer Science, or related fields; knowledge of machine learningBachelor's degree in Statistics, Mathematics, or related fields; proficiency in data visualization and analysis tools
Work EnvironmentResearch-focused, developing models, exploring large datasetsBusiness-focused, interpreting data, creating reports and dashboards
Employer & Industry UsageTech companies, research institutions, large enterprisesRetail, finance, healthcare, marketing

While both roles analyze data, Data Mining Scientists focus on developing predictive models and algorithms from large datasets, often in research or development settings. Data Analysts interpret data to generate reports and insights for business decisions. The roles complement each other but differ in technical depth and focus areas.

Is 40 too late for data science?

Data mining scientists and data scientists can enter the field at any age, as success depends on skills, experience, and continuous learning. Many professionals transition into data science later in their careers by acquiring relevant knowledge in programming, statistics, and tools like Python or R. Age is not a barrier if you develop the necessary expertise and stay current with industry trends.

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

To thrive as a Data Mining Scientist, you need a strong background in statistics, data analysis, and programming, usually supported by a degree in computer science, mathematics, or a related field. Expertise with tools and languages such as Python, R, SQL, and machine learning frameworks (e.g., scikit-learn, TensorFlow), as well as experience with big data platforms like Hadoop or Spark, is essential. Strong problem-solving abilities, communication skills, and curiosity help you uncover insights and present findings effectively. These skills are crucial for extracting valuable information from complex datasets, driving data-driven decisions, and supporting organizational goals.

How does a Data Mining Scientist typically collaborate with other departments within a company?

Data Mining Scientists often work closely with cross-functional teams, including data engineers, business analysts, and product managers. They collaborate to define project goals, understand data requirements, and translate business needs into actionable data models. Effective communication is key, as Data Mining Scientists must explain complex findings in an accessible way and work together to implement data-driven solutions that support business objectives. This collaborative environment fosters innovation and ensures that insights are aligned with broader company strategies.

What does a Data Mining Scientist do?

A Data Mining Scientist analyzes large sets of data to discover patterns, trends, and insights that can help organizations make informed decisions. They use statistical methods, machine learning algorithms, and programming tools to extract useful information from complex data sources. Their work often involves data cleaning, feature selection, model building, and interpreting results for non-technical stakeholders. Data Mining Scientists are essential for turning raw data into actionable knowledge across many industries, including finance, healthcare, and marketing.

Is data mining a good career?

Data mining is a viable career as a Data Mining Scientist involves analyzing large datasets to extract useful patterns, often requiring skills in statistics, programming, and data visualization tools. The field offers opportunities in various industries such as technology, finance, and healthcare, with demand for professionals who can turn data into actionable insights.
More about Data Mining Scientist jobs
Infographic showing various Data Mining Scientist job openings in the United States as of June 2026, with employment types broken down into 35% Full Time, 3% Part Time, 6% Temporary, and 56% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.
Data Scientist (Subject Matter Expert)

Data Scientist (Subject Matter Expert)

Bigbear.ai

Washington, DC

$136K - $240K/yr

Full-time

Posted 12 days ago


Job description

Overview

BigBear.ai is seeking a Data Scientist Subject Matter Expert (SME) to lead a team of data scientists and engineers conducting data analytics, data engineering, data mining, exploratory analysis, predictive analysis, and statistical analysis using scientific techniques to correlate data into graphical, written, visual, and verbal narrative products to enable more informed analytic decisions. The successful candidate will demonstrate a refined ability to define problems, supervise studies, and lead surveys to collect and analyze data to provide advice and recommend solutions. Additionally, the candidate will also demonstrate analytic leadership and expertise in identifying, planning, developing, and executing analytic production methodologies, tradecraft, and techniques aligned with the customer’s mission. This position will be based out of Washington, D.C. or the greater National Capital Region (NCR) and is an opportunity to get in on the “ground level” of a new and exciting program with one of our customer.


Responsibilities

In addition to the above, duties for this position typically include: creating various ML-based tools or processes, such as recommendation engines or automated lead scoring systems. Perform statistical analysis, apply data mining techniques, and build high quality prediction systems. The successful candidate should be skilled in data visualization and use of graphical applications, including Microsoft Office (Power BI) and Tableau; major data science languages, such as R and Python; managing and merging of disparate data sources, preferably through R, Python, or SQL; statistical analysis; and data mining algorithms. Additionally, the candidate should have prior experience with large data Multi-INT analytics, ML, and automated predictive analytics.


Qualifications

  • Must possess a TS/SCI clearance with a CI poly

  • Master’s degree in data science, data engineering, mathematics, or another related field (an additional 5 years of experience may be substituted for this requirement)

  • Minimum of 12 years of experience conducting analysis using data science or engineering, with at least a portion of experience within the last 2 years

  • Deep understanding and experience using Python, R, and/or SQL

  • Prior experience with large data, multi-INT analytics, machine learning, and automated predictive analytics

  • Demonstrable leadership and management experience on teams of junior to mid-range data scientists, engineers, or analysts