Vetted Dashboard Development Professionals

“Talent Acquisition/Recruiting Operations leader with 10+ years driving large-scale K-12 district hiring, including staffing across 200 schools and managing thousands of candidates annually. Known for redesigning fragmented recruiting workflows and implementing ATS solutions (Lever, AppliTrack, Taleo, Oracle HCM) to deliver measurable gains: 15% vacancy reduction, 20% faster time-to-hire, 30% fewer compliance errors, and 25% faster onboarding.”

“Data engineer with experience delivering an end-to-end pipeline handling ~3.5TB in a star-schema setup (fact + dimensions) and producing business-facing tables in Hive/Spark. Identified and resolved UAT-reported duplicate issues caused by joins through root-cause analysis, and also built automation to run Spark SQL metrics on weekly/monthly/quarterly cadences and distribute results to users.”

Nikhil Saukhla

Screened

Director-level Operations & Chief of Staff specializing in HealthTech and venture-backed startups

12y exp

“Operations leader/advisor with experience joining a Cedar Sinai Accelerator spinout (RAIOS) at an inflection point and rebuilding the company’s internal ops “connective tissue” across HR, finance, IT, product, and sales. Uses structured frameworks (RACI, OKRs/KPIs), rapid diagnostics, and tool centralization (Gusto, BILL, Brex) to create scalable, founder-friendly operating systems.”

Sri Harshitha Yannam

Screened

Junior Software Engineer specializing in AI/ML and cloud platforms

Austin, TX2y exp

“LLM/agent engineer who shipped a production "Memory Assistant" at HydroX AI, building a LangChain/LlamaIndex RAG memory pipeline on ChromaDB/FAISS with robust fallbacks (BERT/BART), prompt-injection mitigation, and 99.9% uptime monitoring. Also built a multi-step customer support agent using Rasa + OpenAI Assistants API with structured tool calling, guardrails, and human-in-the-loop escalation, and has experience hardening agents against messy ERP data via Pydantic validation, idempotency, and transactional outbox patterns.”

“Data platform engineer focused on large-scale, real-time fraud systems, with hands-on ownership of streaming architectures using Kafka, Spark, Snowflake, and Databricks. Stands out for combining performance tuning and platform automation with LLM/RAG-based enrichment, delivering measurable gains in latency, fraud accuracy, false positives, and analyst decision speed.”

“Healthcare analytics professional with experience at UnitedHealth Group, focused on turning messy claims, eligibility, and provider data into clean reporting datasets and Power BI dashboards. Combines SQL and Python automation with strong stakeholder alignment around KPI definitions, helping operations teams improve claim turnaround visibility and cost efficiency.”

“Analytics candidate with hands-on experience at AT&T building SQL/Python pipelines for churn, usage, billing, and network-performance data at multi-million-row scale. Stands out for combining strong data quality and reconciliation practices with measurable operational impact, including a 30% query runtime improvement and ~8 hours/week of reporting automation savings.”

Saisureshreddy Challa

Screened

Mid-level Data Scientist specializing in AI/ML, LLMs, and domain analytics

California, USA6y exp

“BlackRock AI/ML engineer who built and owned a production LLM document intelligence system for regulatory and investment analysis end-to-end. They combined RAG, multi-agent validation, strong evaluation/monitoring, and reusable Python services to process 50K+ documents, cut review time 40-50%, and improve decision accuracy by about 25%.”

Thomas Le

Screened

Junior Full-Stack Software Developer specializing in web, mobile, and health tech

Remote2y exp

“Developer who uses AI as a productivity accelerator while maintaining strong ownership of code quality, security, and readability. Built an AI-powered planning tool during the PolyPrompt hackathon that transformed messy project requirements into structured tasks, timelines, and assignments, and has also led human teams through Veggie Rescue with a focus on user-aligned execution.”

“State Street engineer who identifies operational pain points and turns them into high-impact internal platforms, including a service-health monitoring system and a Databricks log standardization pipeline used by 200+ users. Also experiments with practical LLM workflows, having built a Claude-based AI host that dramatically reduced facilitation time for a growing book club.”

“LLM/agent engineer who shipped a two-stage AI recruitment screening platform at Foursquare that automated resume ingestion through behavioral assessment, delivering an 85% reduction in screening time across 5,000+ applications with auditability and confidence-gated decisions. Also built a multi-agent benchmarking framework using MCP tool interfaces and a RAGAS + LangSmith evaluation/observability stack, including async re-architecture that cut production latency by 50%.”

Cassandra Pizarro

Screened

Mid-level Software Engineer specializing in frontend and integrations

Mountain View, CA7y exp

“Frontend-leaning product engineer with strong ownership in fintech integrations, including leading the first global PayPal integration on QuickBooks and enabling 20,000+ non-U.S. users across UK, Canada, and Australia. Brings a mix of React/TypeScript architecture, API collaboration, and domain depth in accounting workflows like VAT and Chart of Accounts mapping.”

“Manager at Prophet with 5 years in management consulting, spanning growth strategy, monetization, market expansion, and go-to-market work for clients including Netflix, AstroTurf, PwC, and Success Academy. Stands out for combining mixed-method research, analytics, and cross-functional execution to drive measurable outcomes, including an 18% improvement in teacher retention and pilot-based rollout strategy work at Netflix.”

“Built and deployed a production LLM/RAG clinical decision support system that enables real-time semantic search over unstructured EHR notes and delivers patient risk insights. Strong in healthcare-grade MLOps and compliance (HIPAA, PHI handling, encryption, RBAC, audit logs) and scaled embedding/retrieval pipelines using Spark/Databricks and Airflow. Partnered with clinicians via Power BI dashboards and explainability, contributing to an 18% reduction in patient readmissions.”

“Recruiting Operations/Talent Ops leader who owns end-to-end TA process, tech stack, and vendors, with experience managing both small direct teams and 20+ person matrix groups. Led complex compliance-focused workflow redesigns (including consent and candidate-to-req linking with 97% completion in 24 hours) and served as TA project manager for a PeopleSoft-to-Workday HCM transition while keeping the ATS running, aligning US/Canada process differences through security and routing.”

“Built and deployed a production LLM-powered internal documentation assistant using embeddings, a vector database, and a RAG pipeline to reduce time spent searching PDFs/manuals. Experienced in orchestrating end-to-end LLM workflows with Airflow/LangChain, improving reliability via monitoring/error handling, and driving measurable quality through retrieval and hallucination-focused evaluation metrics.”

“Senior Membership Manager at Chief who operated in a player/coach leadership role across US/UK teams. Partnered with CRO and RevOps to shift the business from a city-by-city model to a national GTM, scaling membership from 3,400 to 20,000+ and lifting conversion 10% through revamped workflows, enablement, and data-driven KPI dashboards.”

“Talent Ops/TA leader who has managed a 15-person combined recruiting + operations team and owned major HR tech initiatives, including end-to-end CRM implementations (Phenom People, GEM) and ATS/HRIS compensation-field integrations (PeopleSoft to Taleo). Known for measurable process improvements—cut time-to-fill from 100 to 65 days, increased offer acceptance by 20%, and boosted referrals by 30%—and for building analytics dashboards to pinpoint funnel bottlenecks and hiring manager responsiveness.”

“Data/ML practitioner with experience applying NLP and classical ML to large-scale customer data (2B+ records) for segmentation, prediction, and survey-text classification, delivering measurable business impact (~18% engagement efficiency). Has hands-on entity resolution across multi-source datasets and has built embedding-based semantic search using SentenceBERT + a vector database with domain fine-tuning (~20% relevance improvement), plus production workflow experience with Spark/Airflow and cloud tooling (AWS/Azure).”

“Operations and general management leader with experience spanning Citibank (Regional VP), a startup COO/GM role, and industrial operations at Tatco. Has delivered high-impact operational and technology changes including a Paychex payroll migration for 150+ employees and an ERP/subscriber migration of 200,000+ records that improved marketing execution and sales enablement, while also managing executive alignment and sensitive workforce matters.”

Wei Jiang

Screened

Junior Machine Learning Engineer specializing in MLOps and statistical modeling

Greenwood, SC3y exp

“Integration engineer at ES Foundry who led deployment of ELsentinel, a production EL image-based solar cell quality monitoring system using a Swin Transformer classifier (>0.8 F1 across 15+ classes) plus a live real-time prediction dashboard. Strong in solving messy labeling/data-quality problems with process-team collaboration and shipping ML systems despite limited compute/infrastructure.”

Mohammad Husain

Screened

Mid-level Performance Marketing & User Research Specialist in E-commerce growth

Shanghai, China6y exp

“Growth and creator/affiliate partnerships operator with Temu experience scaling gamified in-app referral/retention loops (Fishland, Lucky Flip). Built relationships with top, sometimes “black-hat,” affiliates via Discord/Reddit, extracted and systematized winning tactics through A/B/multivariate testing, then scaled them through paid channels. Also brings a personal creator network from a student-founded business plus Instagram/TikTok pages totaling 1M+ followers to ramp campaigns quickly and drive strong ROAS.”

Naga Manasa Bandaru

Screened

Mid-level Frontend Software Engineer specializing in React, Next.js, and TypeScript

Dallas – Fort Worth, TX4y exp

“Product-focused full-stack engineer with FedEx experience building an internal logistics dashboard for near real-time shipment status and performance metrics using Next.js App Router + TypeScript. Strong in production ownership and performance work—uses React Profiler/Chrome DevTools to eliminate expensive re-renders and applies Postgres indexing/query tuning validated via EXPLAIN ANALYZE to improve dashboard responsiveness.”

pavan kalyan padala

Screened

Mid-level Data Scientist specializing in predictive and generative AI

Daytona Beach, Florida4y exp

“AI/ML engineer with production LLM experience in regulated financial services (J.P. Morgan Chase), building a customer response engine to automate first-contact resolution while addressing privacy, bias, compliance, and scale. Strong MLOps/orchestration background (Airflow, Docker/Kubernetes, AWS Step Functions, Azure ML/SageMaker) plus proven ability to integrate with legacy systems and drive stakeholder adoption through dashboards, auditability, and training.”