Freelance Data Scientists in United States
Freelance Data Scientists in United States
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Ari Harrison
pro
San Francisco, USA
AI & ML Engineer
$1k+
Earned
7x
Hired
28
Followers
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AI & ML Engineer
1
BioBERT Attention Visualization Tool An interactive web application for visualizing attention mechanisms in BioBERT on biomedical text. This tool helps researchers and practitioners understand how transformer models process biomedical language by providing intuitive visualizations of attention patterns.
1
115
1
Open-source REST API for molecular dynamics simulations, protein-ligand docking, and conformational analysis. Features SMILES to OpenMD Conversion: Convert SMILES strings to OpenMD format files with real 3D optimization Comprehensive Property Calculation: 32+ molecular descriptors calculated from real 3D coordinates Multiple Force Fields: Support for AMBER, CHARMM, OPLS, and GROMOS force fields Real Calculations Only: No mock data - all properties derived from actual 3D structures
1
131
2
Clinical Trial Success Predictor
2
132
1
Tesla Stock Price Dashboard
1
47
Data Scientist
(4)
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Solomon Bilancieri
Florida, USA
Transforming data into compelling stories with PowerBI
5.0
Rating
3
Followers
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Transforming data into compelling stories with PowerBI
1
Optimizing Sales Data with PowerBI
1
44
1
VideoGame Tool - What to Train Next Determination Tool using API
1
40
1
Microsoft PowerBI Dashboards/Reports
1
40
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(3)
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VJ Sojitra
Columbus, USA
AI Engineer | Agentic Systems & Automation | MLOps
New to Contra
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AI Engineer | Agentic Systems & Automation | MLOps
0
I developed an AI-assisted document-intelligence workflow for transportation-agency teams working with large collections of reports, standards, studies, scanned documents, and project records. The system combined document extraction, OCR, structured metadata, semantic retrieval, knowledge relationships, and grounded LLM responses. Analysts could ask questions in natural language, review the supporting evidence, inspect source citations, and approve, revise, or reject generated findings. The workflow was designed around human review, access controls, traceability, and safe failure rather than treating an LLM response as an unquestionable answer. Related work reduced decision time by approximately 60% and improved data accuracy by approximately 35%. The displayed architecture and interface are sanitized representations and contain no client documents, production data, proprietary prompts, or confidential system details.
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117
1
I engineered a large-scale package-network intelligence pipeline using Azure Databricks and PySpark. The system joined approximately 4.5 billion historical records and transformed them into reusable fingerprint signals covering package movement and network behavior. I developed time-windowed feature logic using native Spark expressions rather than Python UDFs, preserving distributed performance at scale. The pipeline produced an approximately 200-million-row fingerprint dataset and a 22-million-row operational output that classified package activity along a cold-to-hot temperature scale. The resulting signals supported downstream monitoring, prioritization, and operational analysis. The architecture shown here is a sanitized representation; client identifiers, proprietary schemas, infrastructure paths, and business rules have been removed.
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154
1
Last week I shipped a full learning platform: two audience journeys (students + tutors), subscriptions and digital-product sales, lead capture, blog — built solo, end to end.
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111
0
I designed and engineered a hierarchical multi-agent orchestration framework for coordinating complex AI-assisted engineering and analytical work. A central orchestrator assigns bounded tasks to specialized builder, analyst, reviewer, and verification agents. Execution follows an explicit dependency graph, while shared evidence, acceptance gates, negative-path testing, and checkpointed state prevent agents from declaring work complete without proof. The framework supports targeted retries, rollback, and recovery from the first incomplete node instead of restarting an entire workflow. It also separates implementation from independent review, reducing the risk of an agent validating its own unsupported conclusions. This independent engineering project demonstrates how agentic systems can be made more controlled, observable, and recoverable. The architecture and control interface are representative views of the framework rather than screenshots containing private execution data.
0
51
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(2)
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Yan Vishnepolsky
Honolulu, USA
Quant & Qual Bilingual User Experience (UX) Researcher🔬
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Quant & Qual Bilingual User Experience (UX) Researcher🔬
1
Email Study for a University, 2021
1
8
1
Card Sort Study
1
7
1
UX Research Democratization, 2023
1
8
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Nima T
Pasadena, USA
Ph.D. EE | Data Science & ML, Intelligent Energy Systems
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Ph.D. EE | Data Science & ML, Intelligent Energy Systems
0
Semi-Supervised Event Identification in Electric Power Systems
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25
0
A Machine Learning Framework for Event Identification
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6
0
Algorithm for Source Localization in Linear Dynamical Systems
0
6
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Ivy Zhou
Atlanta, USA
Web Dev and Data Integration Expert
5.0
Rating
29
Followers
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Web Dev and Data Integration Expert
1
Content, Image and Video Creation
1
41
0
Odoo Sites Hosted Affordably on Google Cloud, AWS, DigitalOcean
0
45
0
Data Pipeline and Embeddable Visual Widgets Using APIs
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35
0
Feed Player: An Interactive UI Tool for Image and Video Display
0
41
Data Scientist
(2)
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The Fantôme Collective
United States
In obscuro astra nascuntur
5.0
Rating
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In obscuro astra nascuntur
0
Business Analytics (BI) implementation
0
12
0
In obscuro astra nascuntur.
0
23
0
Full Rebranding for a leading B2B Services Provider
0
33
0
Ghostwriting for blogs and social media
0
7
Data Scientist
(2)
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Krista Courtaway
Austin, USA
Data Scientist
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Data Scientist
0
News Authenticator NLP
0
11
0
Covid-19 SQL Analysis
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20
0
Austin Housing Analysis
0
11
0
Medical Insurance Premium Prediction
0
23
Data Scientist
(4)
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