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Master Data Scientist Jobs (NOW HIRING)

... science-based solutions for the health and nutritional needs of the world. Balchem employs ... The D365 Master Data Manager is responsible for the governance, integrity, and optimization of ...

Manager, Master Data

Montvale, NJ · On-site

$110K - $135K/yr

... science-based solutions for the health and nutritional needs of the world. Balchem employs ... The D365 Master Data Manager is responsible for the governance, integrity, and optimization of ...

... science-based solutions for the health and nutritional needs of the world. Balchem employs ... The D365 Master Data Manager is responsible for the governance, integrity, and optimization of ...

Required : • Bachelors Degree - Computer Science, Mathematics, Statistics, Data Science ... in Master Data Domain like Products, Customers, Suppliers etc. • Experience in building and ...

Bachelors Degree - Computer Science, Mathematics, Statistics, Data Science, Electrical/Computer Engineering or related field required; Master's Degree preferred * Licenses/Certificates/Designations ...

Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or related field (PhD preferred for some roles) * 5+ years of experience in data science or a related field

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Master Data Scientist information

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$46K

$165K

$243.5K

How much do master data scientist jobs pay per year?

As of Jul 12, 2026, the average yearly pay for master data scientist in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

Can you be a data scientist with a master's?

A master's degree in a relevant field such as data science, computer science, or statistics is often sufficient for many data scientist roles. Employers typically value strong analytical skills, programming experience in tools like Python or R, and knowledge of machine learning, which can be gained through a master's program. Additional certifications or practical experience can further enhance job prospects.

How does a Master Data Scientist typically collaborate with cross-functional teams within an organization?

As a Master Data Scientist, you'll frequently work alongside departments such as engineering, product management, and business analytics. Collaboration often involves translating complex data insights into actionable business strategies or product features. You'll also guide less experienced data scientists, ensuring analytical consistency and mentoring junior team members. Effective communication and the ability to present findings to both technical and non-technical stakeholders are key parts of the role.

Is a master's in data science worth it?

A master's in data science can enhance a Master Data Scientist's skills in advanced analytics, machine learning, and data management, often leading to higher-level positions and increased salary potential. However, practical experience and proficiency with tools like Python, R, and SQL are also critical for success in the field. The value depends on individual career goals and the specific industry or company requirements.

What is the difference between Master Data Scientist vs Data Scientist?

AspectMaster Data ScientistData Scientist
Required CredentialsAdvanced degrees (Master's or PhD), specialized certificationsBachelor's or Master's degree, relevant certifications
Work EnvironmentResearch-focused, complex data projects, leadership rolesData analysis, model development, reporting
Employer & Industry UsageTech firms, finance, healthcare, research institutionsStartups, corporations, consulting firms
Search & Comparison IntentHigher expertise, leadership, advanced skillsEntry to mid-level roles, foundational skills

The Master Data Scientist typically has advanced education and handles complex projects, often leading teams or research efforts. Data Scientists usually possess foundational to intermediate skills, focusing on data analysis and model building. The Master Data Scientist role is more specialized and senior, while Data Scientist roles are more common and entry-level to mid-level positions.

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

A Master Data Scientist typically requires advanced statistical knowledge, strong programming skills (such as Python or R), and a graduate degree in a quantitative field. Expertise with machine learning frameworks, big data platforms (like Hadoop or Spark), and data visualization tools, as well as certifications such as Certified Analytics Professional (CAP), are highly valued. Exceptional problem-solving, communication, and leadership skills help drive impactful insights and collaborate across teams. These competencies enable data-driven decision-making and innovation, ensuring that complex analytical projects deliver actionable business value.

Is 40 too late for data science?

Master Data Scientists and other data science professionals can successfully start or transition into the field at age 40 or older. Success depends on acquiring relevant skills such as programming, statistics, and machine learning, as well as gaining practical experience through projects or certifications; age is generally not a barrier in the industry.

What is a Master Data Scientist?

A Master Data Scientist is an advanced-level professional who specializes in analyzing complex data sets to extract meaningful insights, drive strategic decisions, and solve business problems. They combine expertise in statistics, machine learning, programming, and domain knowledge to design and implement sophisticated data models. Master Data Scientists often lead data science teams, mentor junior members, and play a key role in setting data strategy and best practices within an organization. Their work is integral to optimizing processes, predicting trends, and supporting innovation across various industries.

Can data scientists make $300k?

Senior data scientists with extensive experience, advanced skills in machine learning, and proficiency in tools like Python and SQL can earn salaries of $300,000 or more, especially in high-cost-of-living areas or within large tech companies. Achieving this level often requires a combination of expertise, leadership responsibilities, and sometimes stock options or bonuses.
More about Master Data Scientist jobs
What cities are hiring for Master Data Scientist jobs? Cities with the most Master Data Scientist job openings:
What states have the most Master Data Scientist jobs? States with the most job openings for Master Data Scientist jobs include:
Infographic showing various Master Data Scientist job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $165,018 per year, or $79.3 per hour.
Lead, Master Data Management

Lead, Master Data Management

Springs Window Fashions

Middleton, WI • On-site

Full-time

Posted 6 days ago

New


Springs Window Fashions rating

5.3

Company rating: 5.3 out of 10

Based on 6 frontline employees who took The Breakroom Quiz


Job description

Job Summary:
Springs Window Fashions is North America’s premier window covering company, dedicated to creating the Best Experience for all stakeholders. The Lead, Master Data Management will oversee enterprise MDM initiatives, balancing technical execution with functional leadership to design and enhance scalable master data solutions across business processes.
Responsibilities:
• Serve as a functional lead on MDM initiatives, guiding solution design, process definition, stewardship practices, and alignment with MDM standards and governance expectations.
• Mentor and guide MDM Application Developers, MDM Analysts, and business data stewards, supporting skill development, knowledge sharing, and best practice adoption.
• Partner with business stakeholders, Data Engineering, BI & Analytics, Financial Systems, and other IT counterparts to translate master data needs into scalable, governed solutions.
• Coordinate cross-functional MDM workstreams, helping prioritize issues, resolve data and process challenges, and maintain continuity across systems and domains.
• Serve as a backup to the Manager, Master Data Management, or as the primary MDM functional lead when needed, supporting stakeholder engagement, initiative leadership, and MDM delivery continuity.
• Design, develop, and enhance master data solutions, workflows, data models, hierarchies, validation rules, and supporting processes across key enterprise data domains.
• Support the evaluation, selection, and implementation of MDM platforms and tools to enable scalable and sustainable master data management capabilities.
• Ensure MDM solutions support multiple data domains, including customer, product, vendor, financial, and other critical enterprise data.
• Provide technical leadership in defining data models, hierarchies, solution workflows, and supporting structures that enable efficient, governed master data management.
• Collaborate with Data Engineering & Architecture teams to align MDM solutions with enterprise data platforms, integration patterns, and downstream analytics needs.
• Support the definition and adoption of master data standards, ownership models, stewardship workflows, and lifecycle management processes.
• Partner with business data stewards to define data quality rules, validation logic, approval workflows, and maintenance processes.
• Develop and monitor data quality standards, controls, and metrics to improve master data accuracy and consistency.
• Drive root cause analysis and resolution of data quality issues across systems.
• Lead continuous improvement of master data processes, workflows, and controls.
• Collaborate with the Data Warehousing & Integration (DAWGs) team to ensure master data is consistently integrated across enterprise systems and analytics platforms.
• Partner with BI & Analytics teams to support trusted master data for reporting, dashboards, certified datasets, and decision-making.
• Work closely with Financial Systems, Pricing, ERP, and operational teams to align master data structures with business processes and system requirements.
• Support integration of multiple data sources and applications to enable reliable, consistent master data flows across enterprise platforms.
• Contribute to documentation of data flows, source-to-target mappings, data definitions, and integration patterns that support enterprise data consistency.
• Oversee support and drive improvement of MDM applications and processes, including issue resolution, enhancements, performance optimization, and workflow efficiency.
• Ensure appropriate testing and release management practices are followed for MDM solutions to support reliable delivery and operational continuity.
• Maintain documentation of MDM processes, solution designs, data structures, standards, and support procedures to enable knowledge transfer and consistent execution.
• Track solution effectiveness and identify opportunities to mature MDM capabilities toward governed, decentralized maintenance, improved data quality, and scalable stewardship.
Qualifications:
Required:
• 4+ years of progressive experience in master data management, data governance, enterprise application development, or related enterprise data roles.
• Bachelor’s degree in Computer Science, Information Technology, Information Systems, Data Management, Data Science, Business Analytics, or a related field required.
• Professional certifications in data management, data governance, MDM platforms, business analysis, cloud platforms, or related technologies (e.g., Informatica, Microsoft Azure, AWS, or similar) are highly valued.
• Experience translating business requirements into scalable technical solutions, data processes, workflows, validation rules, and data quality controls.
• Experience designing, developing, supporting, or improving master data solutions, data models, workflows, or enterprise data applications.
• Demonstrated commitment to ongoing professional development through training, certifications, conferences, and industry engagement.
• Strong proficiency in SQL and relational database concepts, with experience working with complex, multi-source datasets.
• Familiarity with data governance practices, data quality management, stewardship workflows, and master data lifecycle processes.
• Demonstrated ability to analyze complex data and process issues, perform root cause analysis, and develop practical solutions that improve data accuracy and reliability.
• Experience collaborating across business and technical teams to deliver data-driven solutions aligned with operational, financial, analytical, or enterprise system needs.
• Ability to provide guidance, influence stakeholders, and support alignment across cross-functional teams without relying solely on formal authority.
• Strong communication skills with the ability to explain technical and data concepts to technical and non-technical stakeholders.
Preferred:
• Contribution to MDM or data governance initiatives in an enterprise environment.
• Familiarity with MDM platforms or tools such as Informatica MDM, Reltio, Profisee, SAP MDG, Microsoft-based solutions, or similar technologies.
• Working knowledge of multiple master data domains such as customer, product, vendor, financial, location, or organizational data.
• Background supporting ERP, financial systems, pricing systems, product configuration, or other complex enterprise data structures.
• Exposure to manufacturing, consumer products, or similarly complex environments with configurable products, multi-system data flows, or distributed data ownership.
• Demonstrated ability to mentor technical or business team members, lead workstreams, or act as a lead contributor on data-related initiatives.
Company:
Springs Window Fashions supplies leading retailers and distributors with a complete line of blinds, shades, specialty treatments. Founded in 1939, the company is headquartered in Middleton, USA, with a team of 5001-10000 employees. The company is currently Late Stage.

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