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Data Science Associate Jobs in Dallas, TX (NOW HIRING)

This area provides data science support for internal business partners at State Farm, including ... Establish and leverage a network of associates with business domain and data expertise * Instill a ...

Data Scientist

Frisco, TX · On-site +1

$101K - $198K/yr

Job Summary The Data Science role at Bread Financial delivers best-in-class actionable business ... New associate elected coverage begins on date of hire (with the exception of disability coverage ...

Data Scientist- Senior Associate

Dallas, TX · On-site

$58K - $58K/yr

Drive the delivery of robust data science features by taking ownership of specific modules from development and experimentation through to deployment * Engage in agile ceremonies and contribute to ...

Headquartered in Amelia, Ohio, and with associates located across the United States, we are part of ... Join our dynamic, centralized Data Science team as we execute our AI/ML roadmap! We focus on ...

As a Data Owner Senior Associate, you'll leverage AI and ML to make data AI-ready. You'll be ... Closely collaborate with Engineering and Data Science to productionalize your POCs. * Analyze ...

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Data Science Associate information

See Dallas, TX salary details

$56.9K

$67.3K

$127.6K

How much do data science associate jobs pay per year?

As of Jul 2, 2026, the average yearly pay for data science associate in Dallas, TX is $67,306.00, according to ZipRecruiter salary data. Most workers in this role earn between $58,400.00 and $58,900.00 per year, depending on experience, location, and employer.

How does a Data Science Associate typically collaborate with other departments or teams within an organization?

Data Science Associates frequently work cross-functionally, partnering with teams such as engineering, product management, and business analytics to understand project requirements, share findings, and implement data-driven solutions. Collaboration often involves translating complex data results into actionable insights for non-technical stakeholders, ensuring alignment on project goals and deliverables. This role requires strong communication skills, as associates routinely participate in meetings, present analyses, and gather feedback to refine their models or analyses. Effective teamwork helps ensure that data science initiatives support broader business objectives.

Is 40 too late for data science?

Age is not a barrier to becoming a data science associate; many professionals transition into data science later in their careers. Success depends on acquiring relevant skills such as programming, statistics, and machine learning, often through online courses or certifications, regardless of age.

Is an Associates in data science worth it?

An associate's degree in data science can provide foundational skills in data analysis, programming, and statistics, which may help entry-level candidates qualify for junior data science roles. However, many employers prefer candidates with a bachelor's degree or higher, and practical experience or certifications in tools like Python, R, or SQL can enhance job prospects. The value depends on career goals and the specific requirements of potential employers.

What can I do with an associate's degree in data science?

A Data Science Associate with an associate's degree can work as a data analyst, supporting data collection, cleaning, and basic analysis using tools like Excel, SQL, and Python. They often assist in generating reports, visualizations, and insights under supervision, and may pursue certifications to enhance their skills for more advanced roles.

What are Data Science Associates?

Data Science Associates are early-career professionals who support data-driven projects by collecting, cleaning, analyzing, and interpreting large datasets. They typically work under the guidance of more experienced data scientists and help build predictive models, generate reports, and provide insights to inform business decisions. This role often requires proficiency in programming languages like Python or R, familiarity with statistical methods, and strong problem-solving skills. Data Science Associates play a crucial part in transforming raw data into actionable information for organizations.

What is the role of an associate data scientist?

An associate data scientist supports data analysis and modeling tasks by cleaning and processing data, developing algorithms, and creating visualizations. They often work under supervision to assist in building predictive models and may use tools like Python, R, or SQL to analyze data and generate insights.

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

To thrive as a Data Science Associate, you need strong analytical skills, a solid foundation in statistics and mathematics, and proficiency in programming languages like Python or R, often supported by a degree in data science, computer science, or a related field. Familiarity with machine learning frameworks, data visualization tools, and database systems such as SQL is typically required. Excellent problem-solving abilities, effective communication, and collaboration skills help you translate complex data insights into actionable business strategies. These skills are vital for extracting meaningful value from data and supporting data-driven decision-making within organizations.

What is the difference between Data Science Associate vs Data Analyst?

AspectData Science AssociateData Analyst
Required CredentialsBachelor's degree in Data Science, Statistics, or related field; some roles prefer certifications in data analysis or programmingBachelor's degree in Statistics, Mathematics, or related field; often no advanced certifications required
Work EnvironmentCollaborates with data scientists and engineers; involved in building models and algorithmsFocuses on data collection, cleaning, and reporting; supports decision-making
Employer & Industry UsageUsed in tech, finance, healthcare, and consulting firms for data-driven projectsCommon across various industries for business insights and reporting

The Data Science Associate role typically involves more technical work like building models and applying machine learning, whereas Data Analysts focus on interpreting data and creating reports. Both roles require strong analytical skills, but Data Science Associates often have a deeper understanding of programming and statistical modeling.

What are the most commonly searched types of Data Science jobs in Dallas, TX? The most popular types of Data Science jobs in Dallas, TX are:
What are popular job titles related to Data Science Associate jobs in Dallas, TX? For Data Science Associate jobs in Dallas, TX, the most frequently searched job titles are:
What job categories do people searching Data Science Associate jobs in Dallas, TX look for? The top searched job categories for Data Science Associate jobs in Dallas, TX are:
What cities near Dallas, TX are hiring for Data Science Associate jobs? Cities near Dallas, TX with the most Data Science Associate job openings:
WFP Senior Data Scientist

WFP Senior Data Scientist

JPMorgan Chase & Co.

Plano, TX • On-site

Full-time

Medical, Retirement

Posted 28 days ago


JPMorgan Chase & Co. rating

8.0

Company rating: 8.0 out of 10

Based on 486 frontline employees who took The Breakroom Quiz

54th of 144 rated banks


Job description


If you like turning real-world problems into models that actually move the needle, you'll fit right in. Our Workforce Planning (WFP) Data Science team builds AI/ML solutions that help forecast demand, optimize capacity, and sharpen scheduling-at the scale of Chase call centers, back office operations, and ~5,200 branches. The work is complex, high-impact, and rarely "plug-and-play"-you'll frame the problem, choose the right math, and deliver solutions built for action. If real-time decisioning sounds like your kind of challenge, this is where you belong.
As a Data Scientist Associate Senior within the Consumer and Community Banking in Workforce Planning (WFP) you will solve complex, data-intensive, and often unstructured business problems that materially impact operations. You will independently frame ambiguous questions, translate them into mathematical formulations, and select modeling approaches grounded in strong theoretical fit-not just benchmark off-the-shelf algorithms. You will design, develop, and productionize rigorous AI/ML solutions that advance next-generation capabilities, including moving toward real-time inference and decision-making across Workforce Planning.
Job Responsibilities
  • Design and development of Machine Learning, Artificial Intelligence and Statistical models.
  • Support AI/ML projects individually or part of a project team.
  • Collaborate with stakeholders to understand the business requirements and clearly define the objectives of any solution.
  • Select and apply the appropriate modeling approach based on principled understanding of the problem structure and underlying assumptions, while staying up to data on the latest AI/ML research.
  • Ensure the robustness of any data science solution.
  • Develop and communicate recommendations and data science solutions in easy-to-understand-way leveraging data to tell a story.
  • Work effectively and gain credibility and respect of others including peers, clients and other stakeholders.

Required Qualifications, Capabilities, and Skills
  • Master's Degree with 3+ years or Doctorate (PhD) with 1+ years of experience operating as an data science professional (e.g. data scientist, statistician, or related professions) in a quantitative field: Statistics, Analytics, Data Science, Engineering, Operations Research, Economics, Mathematics, Machine Learning, Artificial Intelligence, and related disciplines.
  • Experience supporting AI/ML projects with multiple team members.
  • Hands-on experience developing statistical models, machine learning models, and/or artificial intelligence models.
  • Foundational understanding of the math and theory behind AI/ML algorithms, with the ability to reason about model assumptions, behavior, and limitations beyond empirical validation.
  • Proficient in data science programming languages like Python, R or Scala.
  • Experience with big-data technologies such as Hadoop, Spark, SparkML, etc. & familiarity with basic data table operations (SQL, Hive, etc.).
  • Demonstrated relationship building skills, with a superior ability to make things happen through the use of positive influence.

Preferred Qualifications, Capabilities, and Skills
  • Advanced expertise with Time Series and Operations Research techniques.
  • Natural Language Processing(NLP)/Natural Language Generation(NLG), Neural Nets, or other ML/AI skills.
  • Prior experience with public cloud technologies such as Amazon Web Services(AWS), Azure or Google Cloud Platform(GCP).
  • Previous experience leading highly complex cross-functional technical projects with multiple stakeholders.

This role is not eligible for visa sponsorship. This role is 5 days a week full time in office.
About Us
Chase is a leading financial services firm, helping nearly half of America's households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs.
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
Equal Opportunity Employer/Disability/Veterans
About the Team
Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We're proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions - all while ranking first in customer satisfaction.
The CCB Data & Analytics team responsibly leverages data across Chase to build competitive advantages for the businesses while providing value and protection for customers. The team encompasses a variety of disciplines from data governance and strategy to reporting, data science and machine learning. We have a strong partnership with Technology, which provides cutting edge data and analytics infrastructure. The team powers Chase with insights to create the best customer and business outcomes.

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