Vetted Dashboard Development Professionals

Pre-screened and vetted.

HK

Mid-level UI Developer specializing in real-time dashboards for FinTech and Healthcare

Miami, FL5y exp
CitadelLindsey Wilson College
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VR

Senior Data Scientist specializing in GenAI, LLMs, and Analytics Engineering

Bengaluru, India7y exp
NextivaSri Shakthi Institute of Engineering & Technology
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KB

Mid-level Financial Analyst specializing in banking and credit-risk analytics

Missouri, USA4y exp
PayPalSaint Louis University
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AG

Mid-level Supply Chain & Program Management Analyst specializing in procurement and analytics

Fremont, CA6y exp
TeslaNorth Carolina State University

Tesla sourcing/supplier readiness professional focused on critical lithium-ion battery components, owning end-to-end supplier onboarding and delivery execution. Uses SQL and Power BI to run integrated readiness plans across samples/approvals/tooling and proactively mitigates cost and import-duty risks while improving supplier performance through structured execution cadences.

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NS

Mid-Level Software Engineer specializing in cloud-native systems, automation, and LLM-enabled robotics

Sunnyvale, CA6y exp
AmazonIndiana University Bloomington

React-focused engineer who built a full-stack analytics/test-metrics dashboard (React frontend + Python backend) and turned common UI pieces (data tables, filter panels, chart wrappers) into a reusable internal component library with docs, examples, and basic tests. Strong on profiling-driven performance optimization (React Profiler, memoization) and on owning ambiguous internal-tool projects end-to-end; now planning to package internal patterns into public open-source components.

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VC

Vyas Cholayil

Screened

Mid-Level Software Engineer specializing in Python automation, DevOps, and microservices

Raleigh, NC5y exp
AnsysNorth Carolina State University

Backend-focused engineer who built an internal wiki LLM chatbot end-to-end using FastAPI, Kubernetes, and ChromaDB vector search, including frontend integration. Also has strong DevOps/migration experience—automating large work-item and repo migrations (Jira/FogBugz/ADO on-prem to cloud) via Python scripts, JSON mappings, REST APIs, and validation test suites.

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AS

Mid-level Technical Consultant specializing in Appian delivery and data/AI workflow automation

Mclean, VA5y exp
AppianUniversity of Illinois Urbana-Champaign

Appian consultant/engineer focused on insurance and financial services modernization and AI-enabled workflows. Built and productionized an AI-driven insurance submission intake system (email ingestion, classification/extraction, HITL review) cutting processing time from 2+ hours to under 10 minutes, and delivered semantic smart search with guardrails and UAT-driven ranking improvements. Also partnered with a global bank CTO org, running sessions with 200+ senior leaders to automate regulatory/board metric reporting via platform integrations and attestation.

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Surya Vardhan - Junior Operations Data Analyst specializing in KPI dashboards and SLA reporting in Seattle, WA

Surya Vardhan

Screened

Junior Operations Data Analyst specializing in KPI dashboards and SLA reporting

Seattle, WA1y exp
AmazonCentral Michigan University

Manufacturing/quality-focused professional with experience at Sikorsky Aerospace supporting aircraft parts production for clients such as Boeing and Cobham. Drove data-driven process improvements (cleaned/visualized production data) and redesigned material usage to cut delays by ~20% and reduce waste, while coordinating across production, inspection, QC, and delivery readiness.

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HK

Mid-level Full-Stack Software Engineer specializing in cloud and data platforms

Boston, MA5y exp
Northeastern UniversityPenn State University

Full-stack engineer with experience spanning Amazon IMDb and Northeastern’s NeuroJSON portal, combining consumer product work with complex scientific data applications. Built IMDb’s streaming providers feature—described as the company’s most impactful feature of 2023—and has hands-on experience with React/Angular, GraphQL, AWS, Python services, and production monitoring.

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Chitra Uppalapati - Entry-level Software Engineer specializing in full-stack and machine learning applications in Sunnyvale, CA

Entry-level Software Engineer specializing in full-stack and machine learning applications

Sunnyvale, CA1y exp
WalmartUniversity of Illinois Urbana-Champaign

Built production Python data integrations and dashboard automation for incident analytics, with a strong focus on data quality, observability, and reliability for leadership-facing reporting. Also translated an ambiguous manual creator evaluation process at startup Spring into an automated predictive scoring feature, showing a blend of backend data engineering, test automation, and cross-functional product thinking.

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TY

Timothy Yeav

Screened

Senior AI/ML Engineer specializing in Generative AI and FinTech

Bronx, NY8y exp
InsitroNew York City College of Technology (CUNY)

Built end-to-end LLM/RAG systems for biological data and scientific literature analysis in a drug discovery setting, helping researchers explore disease insights and treatment hypotheses faster. Combines applied GenAI product work with strong production engineering, including monitoring, retrieval optimization, reusable Python services, and scalable deployment on AWS/Kubeflow.

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AD

Atharva Dani

Screened

Mid-level Full-Stack Engineer specializing in React and Go applications

California, USA3y exp
Arista NetworksBITS Pilani

Engineer with hands-on experience using AI coding tools like Claude Code and Augment in daily development, combined with real-world distributed systems work at Arista Networks. Built or worked on a Go-based platform that separated RBAC, audit logging, and provisioning into asynchronously communicating services, enabling scalable and independently evolving access-control workflows.

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SS

Mid-level Business Data Analyst specializing in Financial Services and Healthcare analytics

USA4y exp
VisaGeorge Mason University

Full-stack engineer (~4 years) who has owned and shipped customer-facing SaaS onboarding and a role-based real-time analytics dashboard using TypeScript/React with a modular backend. Experienced in microservices with RabbitMQ and strong observability practices (correlation IDs, structured logging, queue metrics), and built an internal deployment tracker integrated with CI/CD that replaced manual spreadsheet/Slack processes.

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KP

Kristen Perez

Screened

Senior HR & Talent Acquisition Leader specializing in multi-site, regulated operations

Queens, NY12y exp
DO & COQueensborough Community College (CUNY)

Recruiting leader currently managing a 6-person recruiter team, blending people leadership with hands-on executive search when needed. Experienced partnering with HRBPs and CFO-level stakeholders on workforce planning, compensation/market benchmarking, and strategic hire decisions. Led multi-location standardization and automation of recruiting intake and pre-onboarding to improve speed, consistency, and compliance.

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JJ

Intern Generative AI Engineer specializing in RAG and multi-agent systems

Chicago, IL2y exp
NeuraFlashUniversity of Chicago

Built and deployed a production RAG-based multi-agent chatbot during an internship to help consultants answer client questions and guide users through new IT systems with step-by-step instructions. Demonstrates hands-on experience with LangGraph/LangChain/Google ADK, unstructured document parsing and chunking for RAG, and a reliability-first approach to agent workflows (metrics, fallbacks, human-in-the-loop, guardrails).

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YP

Mid-level AI/ML Engineer specializing in Databricks, MLOps, and real-time fraud detection

The Colony, TX4y exp
DatabricksUniversity of North Texas

ML/LLM engineer building production, real-time fraud detection for financial transactions using a two-tier architecture (fast ML + GPT) to deliver both low-latency decisions and analyst-friendly risk explanations. Experienced orchestrating end-to-end retraining, drift monitoring, and automated model promotion with Databricks Jobs/Workflows and MLflow, and partnering closely with fraud analysts to tune alerts, thresholds, and dashboards.

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Sam McKenzie - Mid-level Business Operations & FP&A professional specializing in RevOps automation and GTM strategy in Remote

Sam McKenzie

Screened

Mid-level Business Operations & FP&A professional specializing in RevOps automation and GTM strategy

Remote7y exp
BuildZoomUC Berkeley

At BuildZoom, led cross-functional alignment to launch a new product (Data Explorer) and grew it from $0 to $1.3M ARR in 12 months. Leverages analytics and BI tooling (HubSpot, Looker, Tableau, Sisense) to build executive dashboards and drive strategic decisions, including redesigning sales incentives to emphasize recurring revenue.

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Shruti Kunwar - Mid-level Marketing Analytics professional specializing in digital growth and customer insights in West Lafayette, IN

Shruti Kunwar

Screened

Mid-level Marketing Analytics professional specializing in digital growth and customer insights

West Lafayette, IN5y exp
Purdue UniversityPurdue University

Growth-oriented marketer with hands-on experience at BASF building B2B demand generation and lead handoff systems in the crop protection sector. Stands out for connecting digital channels, dealer networks, field sales, and customer support into measurable conversion workflows, and for navigating ambiguous initiatives like a farmer loyalty program with practical experimentation and on-ground enablement.

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Sai Karthik Chittamuru - Senior Salesforce Developer specializing in AI systems and enterprise cloud solutions in Pittsburgh, PA

Senior Salesforce Developer specializing in AI systems and enterprise cloud solutions

Pittsburgh, PA15y exp
CRMIT SolutionsCarnegie Mellon University

Salesforce-focused engineer with hands-on experience building Sales Cloud and Service Cloud solutions, including a Zoho billing integration for quote/contract workflows and a multi-panel LWC case management dashboard. Stands out for making practical architecture decisions around middleware vs. custom REST, handling idempotency with upsert patterns, and modernizing legacy Aura patterns with Lightning Message Service.

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Akhil Kunala - Mid-level Software Engineer specializing in backend systems and cloud-native FinTech in Seattle, WA

Akhil Kunala

Screened

Mid-level Software Engineer specializing in backend systems and cloud-native FinTech

Seattle, WA5y exp
AmazonUniversity of North Texas

Amazon engineer with 5+ years of experience who built an AI-assisted log investigation and triage workflow that cut debugging time by about 30% during on-call incidents. Combines observability tooling like CloudWatch and Splunk with Python, prompt engineering, and RAG-based diagnostics, and has practical experience orchestrating agentic AI workflows with a strong human-in-the-loop reliability focus.

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RK

Rutuja Kawade

Screened

Mid-level Software Engineer specializing in cloud infrastructure and distributed systems

Atlanta, GA3y exp
RakutenGeorgia Tech

Cloud infrastructure/product engineer with end-to-end ownership of cloud-native storage/observability products, including taking an internal CMS to Google Cloud Marketplace and scaling to ~40,000 deployments. Strong in Kubernetes-based platforms (Operators, microservices, RabbitMQ) and performance/scalability work (e.g., 200% cluster capacity increase) plus internal tooling that materially improved SRE/QA debugging and release velocity.

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JL

Justin Leung

Screened

Mid-Level Software Development Engineer specializing in interactive ad formats

New York, NY4y exp
AmazonSan José State University

Has experience improving an ad server workflow by standardizing genre selection with templates, enabling reuse across multiple accounts and measuring success via hours of manual labor saved. Also delivered an internal technical demo on a device-metrics-to-AWS-CloudWatch logging workflow using whiteboarding and PowerPoint to onboard a new team.

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SR

Mid-level Data & Business Analyst specializing in analytics engineering and BI

6y exp
AdobeUniversity of Wisconsin–Madison

Data/analytics professional with experience across manufacturing and enterprise environments (Wisconsin School of Business project with CNH Industrial; roles/projects at Ascensia Technologies, S&C, and Adobe). Has hands-on work combining warranty/lifecycle tables with technician free-text notes using TF-IDF + tree models (XGBoost/Random Forest), and deep experience in entity resolution/reconciliation across mismatched financial systems using Python/SQL and fuzzy matching, with production-grade pipeline practices in Azure Data Factory/Databricks.

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