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Pete Melgren

Data Scientist
Former data scientist for the Cincinnati Reds.
Pete Melgren is a data scientist with seven years of experience working on end-to-end predictive analytics projects. He has consulted with cross-industry clients on the use of data science concepts such as machine learning, data mining, business intelligence, and predictive analytics to meet their business needs. As a former data scientist for the Cincinnati Reds, he performed in-depth research of advanced baseball physics measures using statistical techniques that include linear regression, linear classification, mixed models, GAM models, and machine learning methods such as XGBoost. Pete also has advanced knowledge of SQL, R, Python, and AWS.

Rahulraj Singh

Data Scientist
Specializes in technical eBook & documentation.
Rahulraj has over 4 years of experience in technical and non-technical writing including but not limited to published research papers, journal articles, blogs, magazine letters, and newspaper pieces. He excels in performing extensive research and writing clear and crisp content that is understandable for everyone. His philosophy behind writing is to make reading complex topics, fun and intriguing.

Brad Baker

Data Scientist
With e-commerce & payments experience from Coca-Cola.
Brad Baker is a senior business analyst with e-commerce and payments experience. He works for Georgia Pacific in supporting existing systems, Power BI reports, and creating visualization. At Coca-Cola, he supported agile development teams on digital marketing projects including AEM (Web CMS) component enhancements and new capabilities, brand site migrations, and platform upgrades by eliciting and documenting requirements, and analyzing functionality and user flows. He also served as a UX business analyst for Cox Communications where he was responsible for leading analytical project activities for VP-backed technology products. His technical skills include Magento, JIRA, Confluence, SharePoint, VBA, PPT, HTML, CSS, JavaScript, APIs, Tableau, OBIEE, SQL, SPSS, Azure DevOps, Balsamiq, Axure, and Figma, among others.

Aniruddha Madurkar

Data Scientist
Technical writer and data scientist.
Aniruddha Madurkar is a technical writer with a background in data science. He specializes in writing on data science, machine learning, and AI topics. Aniruddha is also a contributor to the data science publication, Towards Data Science. As a senior data scientist, he builds end-to-end enterprise machine learning systems for Fortune 500s and startups. At Fulcrum Analytics, he worked on evolving customer segmentation model for a healthcare and insurance provider to include entire business units, greater explainability, and faster inference.

Marie Weber

Data Scientist
Expert in analytics, content, email marketing, SEO, social media & PPC.
Marie Weber works directly with clients on online marketing campaigns covering analytics, content creation, email marketing, SEO, keyword research, social media, and PPC. She utilizes analytics, CRM data, and market research to build strategic recommendations. At The Food Group, she collaborated with multiple agency teams, including account services, creative, digital, and media, to provide successful marketing campaigns for food manufacturers and commodity boards. Her technology skills include Salesforce, Sugar CRM, Pardot, Marketo, HubSpot, ZoomInfo, Google Analytics, Google Tag Manager, Google Data Studio, WordPress, Sitefinity, Sitecore, Screaming Frog, Moz, Google Ads Editor, and Google Keyword Planner.

Sagar Goli

Data Scientist
Former group manager of data & analytics at Avanade.
Sagar Goli is a data and analytics expert with experience in implementing data warehousing and business intelligence solutions specializing in Microsoft Business Intelligence practice. His fields of expertise include data and analytics, data warehousing, business intelligence, data integration, data governance, master data management, visualizations, and operational reporting. He has worked for big companies such as Avanade, Pfizer, Marlabs, Eli Lilly, and Progressive Insurance.
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Most teams see matched candidates within 48 hours. Our pre-vetted network means we are not starting from scratch when you reach out. If we do not have the right person available, we will tell you upfront rather than scramble.
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Contract talent works on defined projects with clear deliverables. Embedded talent integrates into your team for ongoing work, attending standups and using your tools. Both can transition to full-time if the fit is right. We help you choose based on scope, timeline, and budget.
If it is not working in the first few weeks, we will find you a replacement at no additional cost. We are not in the business of defending bad matches. Most clients never need this because we invest heavily in fit upfront.
We offer flexible engagement models: hourly for short-term projects, monthly retainers for ongoing work, or placement fees for full-time hires. No hidden fees, no long-term contracts unless you want them. Your account manager will walk through options on your discovery call.
Yes. Someone who thrived at Google with dedicated QA, DevOps, and product managers may flounder when they have to wear all three hats. We look for people who have operated at your stage, pace, and level of ambiguity.
Yes, and not just the flashy demo-building part. Our Agent Operations practice includes people who have run AI agents in production and dealt with the messy reality of keeping them reliable, cost-effective, and safe.
Most marketplaces optimize for volume. They send you 10 candidates hoping one sticks. We optimize for fit. We would rather say “we do not have the right person” than waste your time. Our 95% satisfaction rate comes from being selective, not fast.