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Data Scientist Jobs (NOW HIRING)

They are currently seeking a Data Scientist to play a pivotal role in planning, executing, and delivering machine learning-based projects that drive business impact. Responsibilities : • Collect ...

New

A Data Scientist is responsible for working cross functionally in the organization with different groups to assist in data collection plans, to analyze, process, and model data, and to teach data ...

A Data Scientist is responsible for working cross functionally in the organization with different groups to assist in data collection plans, to analyze, process, and model data, and to teach data ...

Data Scientist - Irving, TX - 26-01056 Hybrid, 3 days onsite weekly W2 only accepted, no c2c or 1099 or OPT/CPT 1 year project Company Overview: Req ID: 365619 NTT DATA strives to hire exceptional ...

Data Scientist

Alexandria, VA · On-site

$94K - $141K/yr

Provide data science and advanced data analytics to support federal investigations. * Utilize data mining techniques to find patterns in large data sets * Develop prototype software to meet the needs ...

A Data Scientist represents an effective arbiter of strong technical knowledge and clear communication to inform decision makers and warfighters. Main responsibilities of data scientists include a ...

A Data Scientist represents an effective arbiter of strong technical knowledge and clear communication to inform decision makers and warfighters. Main responsibilities of data scientists include a ...

Data Scientist I supports government and program teams by assisting with data analysis, visualization, and reporting to inform mission, operational, and business decisions under senior supervision.

Job Title- Data Scientist Location- New York, NY 10112 Reporting Type- Onsite W2 candidates only preferred Green Card Holders and US Citizens only preferred Summary This role involves building and ...

Innovizant made up of exceptional data scientists and domain experts with a great experience in Our financial services industry solutions include Credit Risk insights, Customer Churn analysis ...

Brillient is seeking an experienced Data Scientist to join our team supporting a federal contract in Silver Spring, MD. This position requires U.S. Citizenship or a permanent resident and the ability ...

Data Scientist

Washington, DC · On-site

$94K - $141K/yr

Project Summary The Data Scientist will support data-driven decision-making by collecting, integrating, analyzing, and visualizing complex datasets. This role focuses on developing analytical models ...

Innovizant made up of exceptional data scientists and domain experts with a great experience in Our financial services industry solutions include Credit Risk insights, Customer Churn analysis ...

Data Scientist Location: Remote (US-based preferred) Type: Full-time Lumi is seeking a talented Data Scientist to join our growing team. As a Data Scientist at Lumi, you'll be responsible for ...

We are seeking an experienced Data Science Engineer to join our team. The ideal candidate will have strong expertise in data science, machine learning, and AI-driven features that enhance decision ...

Data Scientist I supports government and program teams by assisting with data analysis, visualization, and reporting to inform mission, operational, and business decisions under senior supervision.

Data Scientist

Washington, DC · On-site

$94K - $141K/yr

Project Summary The Data Scientist will support data-driven decision-making by collecting, integrating, analyzing, and visualizing complex datasets. This role focuses on developing analytical models ...

Data Scientist Class Code: IDN03P Pay Grade: IST08 Job Summary The Data Scientist in the State of Arkansas will apply advanced data analysis techniques to solve complex problems and assist in policy ...

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Data Scientist information

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$37.5K

$122.7K

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How much do data scientist jobs pay per year?

As of Jun 5, 2026, the average yearly pay for data 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.

What Do Data Scientists Do?

Data scientists collect, confirm, and interpret data to determine useful information for their employer. They help organizations identify patterns and trends in their data to provide information about lucrative opportunities, necessary improvements, and potential innovations. The information data scientists get from the records they gather helps businesses make major decisions in critical areas, such as product development, sales and marketing techniques, and client retention. Data scientists are highly educated; the majority of them have at least a master's degrees, and many have doctorates. Data scientists are valuable members of organizations in many different industries, including pharmaceuticals, manufacturing, and banking.

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

To thrive as a Data Scientist, you need a strong background in statistics, programming (often Python or R), and data analysis, typically supported by a degree in computer science, mathematics, or a related field. Familiarity with machine learning frameworks, data visualization tools, and big data platforms like TensorFlow, Tableau, and Hadoop, as well as certifications in data science, are highly valued. Excellent problem-solving skills, curiosity, and the ability to communicate complex findings clearly set outstanding data scientists apart. These skills and qualities are crucial for extracting actionable insights from data, driving business decisions, and collaborating effectively with stakeholders.

What are some typical projects Data Scientists work on, and how do they collaborate with other teams?

Data Scientists often work on projects such as building predictive models, analyzing large datasets to uncover trends, and developing data-driven solutions to business problems. They regularly collaborate with cross-functional teams, including software engineers, data engineers, and business analysts, to ensure that their insights are actionable and aligned with business goals. Effective communication and teamwork are essential, as Data Scientists frequently need to present complex findings to non-technical stakeholders and incorporate feedback from various departments.

What are Data Scientists?

Data Scientists are professionals who use statistical, analytical, and programming skills to collect, analyze, and interpret large volumes of data. They extract insights and trends from complex data sets to help organizations make data-driven decisions. Data Scientists often work with machine learning, data mining, and big data technologies to build predictive models and solve business problems. Their work bridges the gap between technical data analysis and actionable business strategy.

What is the job of a data scientist?

A data scientist analyzes large datasets to extract insights and support decision-making using statistical methods, programming, and data visualization tools. They often work with machine learning models and require skills in programming languages like Python or R, as well as knowledge of databases and data analysis techniques.

What is the difference between Data Scientist vs Data Analyst?

AspectData Scientist
Required CredentialsDegree in Computer Science, Statistics, or related field; often requires advanced degrees
Work EnvironmentResearch and development, predictive modeling, machine learning projects
Employer & Industry UsageTech companies, finance, healthcare, consulting firms
Common Search & ComparisonOften compared due to overlapping skills in data analysis and modeling

Data Scientists focus on building predictive models, advanced analytics, and machine learning, often requiring higher-level technical skills and education. Data Analysts primarily interpret existing data, generate reports, and support decision-making with descriptive analytics. While both roles analyze data, Data Scientists handle complex modeling and predictive tasks, whereas Data Analysts focus on data interpretation and reporting.

What cities are hiring for Data Scientist jobs? Cities with the most Data Scientist job openings:
What are the most commonly searched types of Data Scientist jobs? The most popular types of Data Scientist jobs are:
Who are the top companies hiring for Data Scientist jobs? The top employers for Data Scientist jobs are:
What states have the most Data Scientist jobs? States with the most job openings for Data Scientist jobs include:
Infographic showing various Data Scientist job openings in the United States as of May 2026, with employment types broken down into 96% Full Time, 2% Temporary, and 2% Contract. Highlights an 86% In-person, 2% Hybrid, and 12% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.

Full-time

Posted 2 days ago


Job description

Job Summary:
NTT DATA North America is a trusted global innovator of business and technology services. They are currently seeking a Data Scientist to play a pivotal role in planning, executing, and delivering machine learning-based projects that drive business impact.
Responsibilities:
• Collect, clean, and analyze datasets from diverse internal and external sources, applying advanced data wrangling techniques to handle structured, semi-structured, and unstructured data while ensuring completeness, consistency, and accuracy.
• Acquire access to various databases and source systems (SQL, NoSQL, graph databases) and create data pipelines for efficient and repeatable data science projects.
• Apply statistical analysis and visualization techniques (hierarchical clustering, principal components analysis (PCA)) to explore and prepare data.
• Design, develop, and validate machine learning, statistical, and optimization models for classification, regression, clustering, recommendation, and prediction tasks.
• Select appropriate algorithms and models for AI /ML, and rigorously test them for accuracy, robustness, and fairness.
• Perform feature selection and engineering, create predictive variables, and experiment with transformations to enhance performance and interpretability.
• Integrate domain knowledge into ML solutions (e.g., care delivery, financial risk, customer journey, quality prediction, sales, marketing).
• Conduct controlled experiments (A/B and multivariate testing), to evaluate hypotheses, measure workflow changes, and quantify the impact of AI solutions on operations.
• Collaborate with MLOps, data engineers, and IT to evaluate deployment options, and establish best practices around ML production infrastructure.
• Continuously monitor execution and health of production ML models, recalibrating as needed and updating them to reflect new data or changing business conditions.
• Work with cross-functional teams, collaborating with stakeholders to refine objectives, and ensure alignment between technical outputs and strategic goals.
• Create dashboards, and interactive visualizations that communicate results to a wide range of audiences, turning technical findings into actionable recommendations.
• Communicate complex projects, models, and results to diverse audiences, including executives and frontline staff, using storytelling and presentation techniques.
• Stay current with industry research and emerging technologies in AI, machine learning, and optimization, proactively experimenting with new methods and recommending adoption of tools that strengthen analytics capabilities.
• Mentor junior data scientists and analysts, provide guidance on technical approaches and model interpretation, and promote collaboration across teams.
Qualifications:
Required:
• Education: Master's, or PhD in Computer Science, Data Science, Engineering, Statistics, Applied Mathematics, Operations Research, or a related quantitative field.
• 3-5 years of hands-on experience planning and executing end-to-end data science projects with demonstrated impact on clinical or operational outcomes in business environments
• Advanced programming proficiency in Python or R with strong expertise in machine learning frameworks (scikit-learn, TensorFlow, PyTorch) and statistical analysis tools
• Expertise in machine learning and statistical techniques including supervised/unsupervised learning, deep learning, NLP, computer vision, regression models, ensemble methods, and experimental design (A/B testing)
• Strong data engineering capabilities including SQL/NoSQL database programming, distributed computing tools (Hadoop, Spark, Kafka), data pipeline development, and experience with cloud platforms (AWS, Azure, GCP)
• Production ML and MLOps experience including model deployment, monitoring, containerization (Docker, Kubernetes), version control, and applying DevOps principles to data science workflows
• Data visualization and communication excellence with ability to create compelling dashboards (Tableau, Power BI), translate complex technical findings into actionable insights, and present to diverse audiences from executives to frontline staff
• Cross-functional collaboration skills with proven ability to work in agile environments, partner with stakeholders to align technical solutions with business objectives, and mentor junior team members
Preferred:
• Specialization in ML, AI, cognitive science, or data science is highly preferred.
• Healthcare domain knowledge preferred, particularly experience with Epic EHR systems, clinical workflows, and healthcare data standards, along with relevant certifications (Clarity /Caboodle, Google Cloud ML Engineer, AWS ML Specialist)
Company:
NTT DATA, Inc. is a trusted global innovator of business and technology services. Founded in 1988, the company is headquartered in Plano, USA, with a team of 10001+ employees. The company is currently Late Stage.