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Structured Labs Jobs in Wisconsin (NOW HIRING)

Bespoke Labs

Data Engineer

Whitewater, WI · On-site

$112K - $135K/yr

... structure -- observation/action spaces, reward signals, episode logic Experience with data versioning and experiment tracking (DVC, MLflow, W&B, or similar) Comfortable with Docker and cloud ...

Bespoke Labs

Data Engineer

Kenosha, WI · On-site

$113K - $136K/yr

... structure -- observation/action spaces, reward signals, episode logic Experience with data versioning and experiment tracking (DVC, MLflow, W&B, or similar) Comfortable with Docker and cloud ...

Bespoke Labs

Data Engineer

Madison, WI · On-site

$115K - $138K/yr

... structure -- observation/action spaces, reward signals, episode logic Experience with data versioning and experiment tracking (DVC, MLflow, W&B, or similar) Comfortable with Docker and cloud ...

Bespoke Labs

Data Engineer

Green Bay, WI · On-site

$111K - $133K/yr

... structure -- observation/action spaces, reward signals, episode logic Experience with data versioning and experiment tracking (DVC, MLflow, W&B, or similar) Comfortable with Docker and cloud ...

Bespoke Labs

Data Engineer

Menomonie, WI · On-site

$113K - $135K/yr

... structure -- observation/action spaces, reward signals, episode logic Experience with data versioning and experiment tracking (DVC, MLflow, W&B, or similar) Comfortable with Docker and cloud ...

Bespoke Labs

Data Engineer

Racine, WI · On-site

$107K - $128K/yr

... structure -- observation/action spaces, reward signals, episode logic Experience with data versioning and experiment tracking (DVC, MLflow, W&B, or similar) Comfortable with Docker and cloud ...

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Structured Labs information

What is the difference between Structured Labs vs Data Analyst?

AspectStructured LabsData Analyst
Required CredentialsTypically requires a background in data science, programming, or engineering; certifications in data analysis or related fields are commonOften requires a degree in statistics, mathematics, or related fields; certifications like Microsoft Excel or Tableau are beneficial
Work EnvironmentUsually in tech companies, research labs, or startups focusing on data-driven projectsCommonly in corporate settings, consulting firms, or finance sectors analyzing business data
Employer & Industry UsageUsed by tech firms, research institutions, and innovative startupsWidely used across industries like finance, healthcare, marketing, and consulting

Structured Labs and Data Analysts both work with data, but Structured Labs often focus on developing data-driven solutions and research, while Data Analysts primarily interpret existing data to inform business decisions. The roles overlap in skills but differ in scope and application.

What are Structured Labs?

Structured Labs refers to specialized environments or facilities designed to conduct controlled experiments, testing, or research, often in fields such as technology, science, or finance. These labs provide structured processes, protocols, and tools to ensure accuracy and repeatability of experiments. Structured Labs can be found in academic institutions, research organizations, or within companies developing new products and technologies. Their main goal is to facilitate innovation, validate hypotheses, and improve the reliability of results.

What are some typical challenges faced by professionals working in Structured Labs roles, and how can they be addressed?

Professionals in Structured Labs often encounter challenges such as managing complex data sets, ensuring compliance with strict regulatory standards, and collaborating effectively with cross-functional teams like product development and compliance. To address these, it’s important to maintain strong organizational skills, stay updated on regulatory changes, and communicate proactively with stakeholders. Many teams use agile methodologies to facilitate collaboration and regularly hold knowledge-sharing sessions to ensure best practices are followed.

What are the key skills and qualifications needed to thrive as a Structured Labs Analyst, and why are they important?

To thrive as a Structured Labs Analyst, you need strong analytical skills, a background in finance or quantitative fields, and familiarity with structured finance concepts, often supported by a relevant degree. Proficiency with financial modeling tools such as Excel, VBA, and platforms like Bloomberg or Intex, along with certifications like CFA or FRM, is highly valuable. Attention to detail, problem-solving, and effective communication are crucial soft skills in this role. These capabilities enable accurate analysis of complex financial instruments and support sound decision-making in fast-paced, high-stakes environments.
What are popular job titles related to Structured Labs jobs in Wisconsin? For Structured Labs jobs in Wisconsin, the most frequently searched job titles are:
What job categories do people searching Structured Labs jobs in Wisconsin look for? The top searched job categories for Structured Labs jobs in Wisconsin are:
What cities in Wisconsin are hiring for Structured Labs jobs? Cities in Wisconsin with the most Structured Labs job openings:
Structured Labs jobs near you

Data Engineer

Bespoke Labs

Whitewater, WI • On-site

$112K - $135K/yr

Full-time

Posted 13 days ago

Job description

About Us

We are AI researchers and builders who understand how to curate data and RL environments that truly improve models. We curated OpenThoughts, one of the best open reasoning datasets, and have trained SOTA models such as Bespoke-MiniCheck and Bespoke-MiniChart.

We are embarked on a journey to build Environments that are entire digital worlds that can be used to push the frontier of agents.

What You'll Be Working On

You will work directly with our research team on RL environment and task creation for agent training. This means designing observation spaces, action spaces, reward signals, and success criteria for new environments — and building the infrastructure that makes world-scale RL training possible. This is a high-ownership role; you will be building novel systems, not maintaining legacy ones.

Must-Have Skills

3+ years of data engineering experience — pipelines, ETL, data modeling in production or research settings

Strong Python proficiency (numpy, pandas, Parquet, HDF5 are daily tools)

Familiarity with at least one RL framework (Gymnasium / OpenAI Gym, dm_env, or equivalent) and working knowledge of RL environment structure — observation/action spaces, reward signals, episode logic

Experience with data versioning and experiment tracking (DVC, MLflow, W&B, or similar)

Comfortable with Docker and cloud infrastructure (AWS or GCP)

Solid grasp of ML storage formats: Parquet, HDF5, JSON Lines

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