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Data Analytics Masters Jobs (NOW HIRING)

The Manager, Data Analytics is a global people leader within QuidelOrtho' s Global Quality ... Advanced degree (MS, PhD, MBA, or equivalent) in a relevant discipline. * Experience implementing ...

Central Insurance is seeking a Data Analytics Manager to lead a highimpact team responsible for ... Masters' degree in Computer Science or related field and 2 years related experience * Or Bachelor ...

Central Insurance is seeking a Data Analytics Manager to lead a highimpact team responsible for ... Masters' degree in Computer Science or related field and 2 years related experience * Or Bachelor ...

Big Data Analytics Process Greetings for the day! My name is Suneetha from Testing Xperts, we are a ... Masters or Ph.D. in Mathematics, Statistics, Computer Science, Operations Research, Engineering ...

The Data Analytics Manager leads our data and analytics function, helping the organization make ... Masters degree preferred * Strong SQL expertise * Experience working with structured and ...

Bachelor's Degree in Data Science, Computer Science, Mathematics or related field required, Masters Degree strongly preferred * 8+ years of experience in data engineering and data analytics required ...

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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 professional with a master's degree, and why are they important?

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 Masters 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.

Is 40 too late for data science?

Data Analytics Masters professionals can enter data science at any age, as the field values skills and experience over age. Many successful data scientists start or transition into the field later in life, often leveraging prior experience, certifications, and continuous learning to stay competitive.

What kind of jobs can I get 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, and data engineer. These positions involve analyzing large datasets, creating reports, and using tools like SQL, Python, or R to support decision-making across various industries.

What types of real-world projects or collaboration opportunities can Data Analytics Masters 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 AI replacing data analysts?

AI tools are automating certain data processing and analysis tasks, but data analysts are still essential for interpreting complex insights, making strategic decisions, and ensuring data quality. The role of a data analyst involves skills like critical thinking, domain knowledge, and communication, which are not easily replaced by AI. Professionals in this field often need to develop expertise in analytics software, programming languages, and data visualization tools to stay relevant.

What is a Data Analytics Masters job?

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.

Is it worth getting a master's degree in data analytics?

A master's degree 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 more senior roles, but practical experience and certifications can also be valuable in this field.
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Manager/ Sr. Manager - Data Product Management - Supply Chain

Manager/ Sr. Manager - Data Product Management - Supply Chain

Tiger Analytics Inc.

Plano, TX โ€ข On-site

$121K - $159K/yr

Full-time

Posted 2 days ago


Job description

Tiger Analytics is an advanced analytics consulting firm. We are the trusted analytics partner for several Fortune 100 companies, enabling them to generate business value from data. Our consultants bring deep expertise in Data Science, Machine Learning, and AI. Our business value and leadership have been recognized by various market research firms, including Forrester and Gartner.

We are seeking a strategic and execution-focused Data Product Manager to lead the development, modernisation, and scaling of enterprise data products. This role will sit at the intersection of business, data engineering, analytics, and technology, translating complex business needs into scalable data solutions that drive measurable impact.

Responsibilities:

  • Work directly with client stakeholders to translate business problems into high-level analytics solution designs.
  • Develop customer understanding through customer data, contributing to the overall analysis of the consumer path to purchase.
  • Develop end-to-end solutions based on an in-depth understanding of business problems to ensure analytics solutions are delivered efficiently, predictably, and sustainably.
  • Responsible for managing analytics projects, collaborating with client stakeholders and Tigerโ€™s team situated globally
  • End-to-end Data + Analytics delivery execution ownership and optimization of resource assignment, sequencing, and allocation.
  • Oversee the design, building, and managing of how business-ready data lives within the Enterprise Data Foundation.
  • Drive coordination between Domains, Products and Projects to help drive reuse and reduce redundancy/duplication in the D+A and broader client portfolio.
  • Responsible for making presentations to senior management, communicating results to business teams, and developing plans to help operationalize analytic solutions.
  • Build data roadmaps to meet hydration targets and support timely delivery for global data initiatives and programs.
  • Ensure data cataloguing in the Data Foundation is accessible to business stakeholders.
  • Work with program Technical Data Product Managers to ensure expectations from D+A are managed and to eliminate disconnects regarding what can be addressed.

Requirements

  • 8โ€“12 years of progressive experience across product management, data analytics, data science, and data management within business-facing environments.
  • Minimum 7 years of experience in Product roles or in a Data Product Manager or Senior Business Analyst capacity with ownership of end-to-end data initiatives.
  • Proven experience owning the full lifecycle of data products โ€” from ideation, business case development, and roadmap definition to MVP launch, scaling, and continuous optimization.
  • Strong expertise in cloud platforms (AWS preferred) and modern data ecosystems, including Snowflake, MongoDB, or similar technologies.
  • Demonstrated experience leading data migration and modernization programs (e.g., legacy to cloud-based architectures).
  • Advanced SQL proficiency with strong understanding of data modeling, data architecture, and analytics frameworks.
  • Hands-on experience working in Agile environments, including backlog management, sprint planning, estimation, and delivery using tools such as JIRA.
  • Proven ability to translate complex business requirements into structured epics, user stories, and technical documentation that enable efficient cross-functional delivery.
  • Experience collaborating with cross-functional teams including Product Owners, Data Engineers, Developers, Testers, and Analytics teams.
  • Strong executive presence with the ability to engage VP-level and senior stakeholders, translating business problems into high-level analytics and data solution approaches.
  • Demonstrated ability to identify high-value analytics opportunities across core business domains (e.g., marketing, risk, operations) and define measurable paths to value realization.
  • Experience driving innovative, business-oriented solutions using advanced analytics, feature engineering, and machine learning techniques.
  • Strong people leadership capabilities, with experience building, mentoring, and managing multi-level teams.
  • Excellent communication skills, with the ability to simplify complex technical concepts for both data & analytics teams and non-technical business stakeholders.
  • Graduate degree in Business Analytics, MBA, or equivalent professional experience.

Benefits

Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, fast-growing, challenging and entrepreneurial environment, with a high degree of individual responsibility.

Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.