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Senior Data Annotation Analyst Jobs in Wisconsin

The Senior Analytics and Platform Analyst will play an important role in driving data-driven decision-making and digital enablement across the organization. You are responsible for delivering ...

Sr. Data Engineer

Madison, WI

$115K - $138K/yr

As a Senior Data Engineer, this seasoned professional will demonstrate competence and creativity in ... Working in our Data Engineering teams, you will collect and analyze data to develop robust ...

Sr. Data Engineer

Madison, WI · On-site

$115K - $138K/yr

As a Senior Data Engineer, this seasoned professional will demonstrate competence and creativity in ... Working in our Data Engineering teams, you will collect and analyze data to develop robust ...

Sr. Data Engineer

Madison, WI

$115K - $138K/yr

As a Senior Data Engineer, this seasoned professional will demonstrate competence and creativity in ... Working in our Data Engineering teams, you will collect and analyze data to develop robust ...

As a consequence you will apply and/or learn a wide variety of statistical techniques including time series analysis, high dimensional clustering, machine learning, data mining and Bayesian modeling.

Work closely with business analysts and product owners to validate model semantics and usability ... Experience * 7+ years of progressive, hands-on experience in data modeling is required for Senior ...

$211K - $246K/yr

Qualifications * 6+ years of professional experience in data engineering and analytics including 2+ years experience leading teams of Sr. Data/Analytics Engineers. * Data leadership experience:

Senior Data Engineer (Remote)

Menomonee Falls, WI · On-site

$123K - $162K/yr

About the Role As Senior Software Engineer, you will collaborate closely with design, product and ... Write complex SQL queries for advanced data transformation, aggregation, and analytics optimization ...

Senior Data Engineer - IGEN

Appleton, WI · On-site

$103K - $140K/yr

POSITION SUMMARY The Senior Data Engineer is the technical leader for IGEN's Data Foundation ... Partners with the Director, Data & Analytics on the Center of Excellence operating model ...

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Showing results 1-20

Senior Data Annotation Analyst information

Is it difficult to get a job at data annotation?

Securing a position as a Senior Data Annotation Analyst typically requires attention to detail, familiarity with annotation tools, and basic understanding of data labeling processes. While some roles may require prior experience or specific skills, entry-level positions are often accessible with relevant training or certifications. The difficulty varies depending on the company's requirements and the competitiveness of the job market.

Does data annotation actually pay well?

Data annotation analysts typically earn hourly wages that are considered modest compared to other tech roles, with pay often ranging from minimum wage to around $15-$20 per hour depending on experience and location. While some companies offer bonuses or flexible schedules, overall compensation for entry-level data annotation positions is generally lower than more specialized data science or engineering roles.

What are Senior Data Annotation Analysts?

Senior Data Annotation Analysts are experienced professionals who oversee the process of labeling and tagging data, such as text, images, or audio, to train machine learning models. They are responsible for ensuring high-quality annotations, developing guidelines, and often mentoring junior annotators. Their work is crucial for the success of AI and machine learning projects, as accurate data annotation directly impacts model performance. Senior analysts also collaborate with data scientists and engineers to refine annotation processes and improve data quality.

What does a data annotation analyst do?

A data annotation analyst labels and categorizes data such as images, text, or videos to help train machine learning models. They use tools and guidelines to ensure data is accurately annotated, which is essential for developing reliable AI systems. Attention to detail and understanding of data formats are important in this role.

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

To thrive as a Senior Data Annotation Analyst, you need expertise in data labeling, analytical thinking, and a strong understanding of machine learning concepts, often supported by a relevant degree or significant experience in data operations. Familiarity with annotation platforms (like Labelbox or Supervisely), data management tools, and quality assurance processes is typically required. Attention to detail, problem-solving, and the ability to communicate feedback effectively are crucial soft skills for this role. These competencies ensure high-quality data sets that drive accurate machine learning models and improve project outcomes.

How does a Senior Data Annotation Analyst typically collaborate with machine learning engineers and data scientists?

As a Senior Data Annotation Analyst, you will often work closely with machine learning engineers and data scientists to ensure that labeled data meets project requirements and quality standards. You may participate in meetings to discuss annotation guidelines, clarify ambiguous cases, and provide feedback on data challenges that arise. Your expertise in annotation tools and processes helps streamline workflows and ensures that the annotated datasets are reliable, which is critical for model training and evaluation. Collaboration is key, and you'll be expected to communicate effectively across teams to address issues and continuously improve the data pipeline.

What is the difference between Senior Data Annotation Analyst vs Data Annotation Specialist?

AspectSenior Data Annotation AnalystData Annotation Specialist
CredentialsBachelor's degree in related field, experience in data annotationHigh school diploma or equivalent, entry-level experience
Work EnvironmentCollaborative teams, project management, quality assuranceIndividual tasks, data labeling, basic quality checks
Industry UsageTech, AI, machine learning companiesAI startups, data labeling firms, research projects

The Senior Data Annotation Analyst typically has more experience, handles complex annotation projects, and oversees quality control, whereas the Data Annotation Specialist focuses on basic labeling tasks. Both roles are essential in AI data preparation, but the senior analyst often leads projects and ensures standards are met.

What is the highest salary for data annotator?

The highest salary for a senior data annotation analyst can reach around $70,000 to $90,000 annually, depending on experience, location, and the complexity of annotation tasks. Advanced roles with specialized skills or certifications may offer higher compensation, especially in competitive tech markets.
What are the most commonly searched types of Data Annotation Analyst jobs in Wisconsin? The most popular types of Data Annotation Analyst jobs in Wisconsin are:
What are popular job titles related to Senior Data Annotation Analyst jobs in Wisconsin? For Senior Data Annotation Analyst jobs in Wisconsin, the most frequently searched job titles are:
What cities in Wisconsin are hiring for Senior Data Annotation Analyst jobs? Cities in Wisconsin with the most Senior Data Annotation Analyst job openings:
Senior Operational Excellence Data Analyst

Senior Operational Excellence Data Analyst

Schreiber Foods

Green Bay, WI • On-site

$83K - $105K/yr

Full-time

Re-posted 27 days ago


Schreiber Foods rating

8.2

Company rating: 8.2 out of 10

Based on 75 frontline employees who took The Breakroom Quiz

62nd of 397 rated food and drinks producers


Job description

Job Summary:
Schreiber Foods is seeking a Senior Operational Excellence Data Analyst who will be responsible for achieving operational and functional targets through independent ownership of moderately complex projects. This role involves collaborating with various teams to enhance operational performance and implementing improvements to processes and systems.
Responsibilities:
• Develop and Sustain SFI Data & Operational Excellence Culture Support, coach, and reinforce data-driven decision making and Operational Excellence principles with partners and Team Members.
• Operational Data Enablement & Business Partnership Serve as the bridge between Operations and Schreiber’s technical data teams to translate complex data into actionable insights.
• Partner closely with operations, manufacturing engineering, process engineering, sourcing, packaging engineering, and FP&A to enable plant teams to identify and act on opportunities related to quality, delivery, capacity, and cost.
• Production Data Needs & Use-Case Definition Understand, define, and prioritize the data needs of production teams to support effective business decisions.
• Apply structured improvement methodologies (e.g., Lean Six Sigma) to support cost, quality, and operational performance initiatives through disciplined data use.
• Data Structure Development, Collection, and Preparation Develop, standardize, and maintain data structures and data pipelines that enable reliable data collection from multiple sources.
• Ensure data accuracy, completeness, and consistency to support trusted analytics and KPI reporting.
• Data Exploration, Analysis, and Model Development Apply analytical and statistical methods to explore data, identify trends, and uncover root causes.
• Where appropriate, develop and maintain models to forecast performance and support proactive, data-based decision making.
• Data Visualization, KPI Standards, and Reporting Establish standards and develop clear, intuitive data visualizations using tools such as Power BI.
• Translate insights into visual formats that are easily understood and actionable, including leadership dashboards and plant-floor visualizations (e.g., HMI screens), to drive alignment and execution.
• Training, Enablement, and Capability Building Provide targeted training, standards, and enablement that build Operations’ capability to independently access, analyze, and visualize data.
• Empower partners to adopt best practices in data analytics and visualization to sustain results beyond direct support.
• Cross-Functional Collaboration & Continuous Improvement Leadership Actively collaborate across functions to promote best practices in data access, analytics, and KPI visualization.
• Champion continuous improvement through effective use of data, analytics, and insight-driven problem resolution.
• May be required to perform other job-related tasks.
Qualifications:
Required:
• Bachelor’s degree in Engineering, Data Analytics, Operations or related technical field.
• 7+ years experience in manufacturing/operations, engineering, technical or related area in building and interpreting operational metrics, dashboards, and analysis.
• Proficiency in Excel, SQL, Power BI, and/or Tableau
• Knowledge/proficiency of statistical programming languages like Phyton or commitment to develop proficiency within 12-24 months is expected.
• Data collection, cleaning and governance practices
• Lean and Six Sigma disciplines where applicable
• Problem-solving skills and ability to translate data into action.
• Ownership, self-started mindset; servant mindset
• Desire to grow and take on new challenges and opportunities.
• Travel varies depending on manufacturing needs. Ability to travel 20% - 40% as required.
• Valid driver's license, auto insurance (at least state minimum- more might be required), acceptable driving record per Schreiber Foods discretion, and vehicle that will ensure applicant can meet the travel necessities of the position are required.
• Authorization to work in the country in which the role is based.
Company:
Schreiber provides dairy favorites to people around the globe. Founded in 1945, the company is headquartered in Green Bay, USA, with a team of 10001+ employees. The company is currently Late Stage.

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