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Data Analytics Masters Jobs (NOW HIRING)

TERREPOWER

Manager, AI and Data Analytics

Irving, TX · On-site

Position Summary The Manager, AI and Data Analytics leads the strategy, design, and delivery of ... Master's degree (MBA, MIS, or related). * Familiarity with ITIL, TOGAF, or other enterprise ...

BBB

Manager, AI and Data Analytics

Dallas, TX · On-site

Position Summary The Manager, AI and Data Analytics leads the strategy, design, and delivery of ... Master's degree (MBA, MIS, or related). * Familiarity with ITIL, TOGAF, or other enterprise ...

Mayo Clinic

Master's degree or PhD in a related field (e.g., computer science, data science, business analytics, healthcare informatics, or MBA) is preferred. * Extensive (15-20+ years) experience in enterprise ...

Dollartree

Manager Reporting And Analytics

Chesapeake, VA · On-site

$125K - $141K/yr

Analyze key data / metrics to identify trends and risks; developing mitigation solutions and ... Master's Degree in Analytics, MBA, or related advanced degree desired but not required Experience ...

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Data Analytics Masters information

What is the difference between Data Analytics Masters vs Data Analyst?

AspectData Analytics MastersData Analyst
CredentialsTypically requires a master's degree in data science, analytics, or related fieldUsually requires a bachelor's degree in a related field; certifications can enhance prospects
Work EnvironmentAcademic, research, or advanced industry roles; often involves project-based workBusiness environments, working with data to generate reports and insights
Industry UsageUsed in academia, research institutions, and advanced analytics roles in industryCommon across industries like finance, healthcare, marketing, and technology

In summary, a Data Analytics Masters is an advanced qualification often required for specialized or research roles, while a Data Analyst is a more entry-level or mid-level position focused on analyzing data to support business decisions. Both roles share overlapping skills but differ in educational requirements and scope of work.

What are the key skills and qualifications needed to thrive as a data analytics master?

To thrive as a Data Analytics professional with a master's degree, you need strong analytical skills, expertise in statistics, and advanced knowledge of data modeling, typically supported by a relevant STEM degree. Proficiency with tools such as SQL, Python, R, Tableau, and familiarity with machine learning platforms is commonly required, along with certifications like Google Data Analytics or Microsoft Certified: Data Analyst Associate. Excellent problem-solving abilities, critical thinking, and effective communication skills help translate complex data findings into actionable business insights. These skills and qualifications are essential for transforming raw data into strategic decisions that drive organizational success.

What is a data analytics master's degree?

A Data Analytics Masters degree is a graduate-level program that focuses on teaching students advanced skills in analyzing, interpreting, and visualizing data to help organizations make data-driven decisions. The program typically covers topics such as statistics, machine learning, data mining, data visualization, and programming languages like Python or R. Graduates are prepared for careers in data science, business analytics, and related fields, where they can apply analytical techniques to solve real-world problems. This degree is ideal for individuals who want to deepen their understanding of data and pursue specialized roles in analytics.

What types of real-world projects or collaboration opportunities can a data analytics master expect during their studies?

Data Analytics Masters programs often include hands-on projects where students work with real datasets from industry partners or simulate actual business scenarios. These projects typically involve teamwork, allowing students to collaborate with peers and sometimes with professionals from related fields such as business, engineering, or IT. This collaborative environment helps students develop both technical and communication skills, and provides valuable exposure to industry-standard tools and workflows. Additionally, these experiences can lead to networking opportunities and open doors for internships or job placements upon graduation.

Is a master's in data analytics worth it?

A master's in data analytics can enhance job prospects for data analysts by providing advanced skills in statistical analysis, programming, and data visualization tools like Python and Tableau. It often leads to higher salaries and roles with greater responsibility, making it a valuable investment for those seeking to advance in the field.

What can I do with a master's in data analytics?

A master's in data analytics prepares individuals for roles such as data analyst, data scientist, business intelligence analyst, or data engineer. These roles involve analyzing large datasets, creating reports, and using tools like SQL, Python, or R to support decision-making across various industries.

What is a data analytics master?

A Data Analytics Masters job typically involves analyzing large datasets to extract insights that help businesses make data-driven decisions. Professionals in this role use statistics, machine learning, and data visualization tools to interpret trends and patterns. They commonly work in industries like finance, healthcare, marketing, and technology. Strong analytical skills, programming knowledge (e.g., Python, SQL, R), and expertise in data visualization tools (e.g., Tableau, Power BI) are essential.

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Data Analytics Masters jobs near you
Infographic showing various Data Analytics Masters job openings in the United States as of August 2026, with employment types broken down into 80% Full Time, 10% Part Time, and 10% Contract. Highlights an 80% In-person, and 20% Remote job distribution.

Data Analytics Developer, AVP - Credit and Insurance

Blackstone

Miami, FL • On-site

Full-time

Re-posted 19 days ago

Job description

Job Summary:
Blackstone is the world’s largest alternative asset manager, seeking to create positive economic impact and long-term value. The role involves the analysis, design, implementation, testing, debugging, and deployment of scalable data-driven analytics tools for the Blackstone Credit & Insurance platform.
Responsibilities:
• Responsible for the analysis, design, implementation, testing, debugging and deployment of scalable data-driven analytics tools for the Blackstone Credit & Insurance platform.
• Help build the platform through use data science, statistics, and computer programming.
• Work hand-in-hand with portfolio managers, asset allocators, middle-office operations, data governance, risk, and fund finance teams focusing on creating scalable analytics tooling.
• Build interactive dashboards & apps focused on portfolio risk characteristics with insights for internal managers and external clients.
• Use engineering and/or data science background to help find alpha in complex credit and structured security markets.
• Comfortable working with diverse datasets and transforming unstructured & unclean data into an organized format suitable for data science.
• Proficient with Python and SQL to build a clean and scalable code base that powers the analytical models and generates novel insight from the data.
• Responsible for building interactive data visualization tools using Business Intelligence software like Sigma & Tableau.
• Play an important role in implementing and extending core system architecture and data warehouses using Snowflake & AWS to build a solid foundation for analytics.
Qualifications:
Required:
• Bachelors or Masters degree in a STEM domain (e.g., Engineering, Computer/Data Science or similar).
• 3+ years of experience in data analytics/data science role.
• Proficiency in database design as well as SQL and Python programming languages.
• Work experience with business intelligence applications (e.g., Sigma, Tableau). Work experience with designing and implementing scalable portfolio analytics platforms.
• Familiarity with big data analytical techniques and cloud technologies including Amazon Web Services (AWS) and Snowflake.
• Proficient in programming in Python and SQL to build scalable and clean code base for analytics platforms.
• Expert in database architecture design and performance optimization. Strong skills designing optimal data structures to host diverse financial data sets. Expert in data visualization tools like Sigma & Tableau. Can quickly build large scale complicated visualization platforms.
• Expert in designing core data analytics model with a focus on reusability, data processing performance and data accuracy.
• Knowledge in math and statistics to implement financial simulation models and understanding security/fund risk methodologies.
Preferred:
• Work experience with fixed income investment strategies.
• Experience with web-based application development in React & Typescript with AWS infrastructure (Terraform).
Company:
Blackstone invests in private equity, real estate, credit, infrastructure, insurance, and other alternative assets. Founded in 1985, the company is headquartered in New York, USA, with a team of 1001-5000 employees. The company is currently Late Stage.

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