Vetted Python Professionals

Sundarajan Swaminathan

Screened

Senior Product Marketing Leader specializing in GTM strategy and RevOps analytics

Dallas, TX7y exp

“Growth creative/performance marketer from BYJU'S (India) who runs disciplined creative experimentation across Meta, TikTok, and YouTube. Notably shifted messaging from feature-led to outcome/testimonial-led creative, delivering CPA down 27%, ROAS up 35%, and +11% trial-to-paid conversion, and has experience leading a small creative pod (editors + writer) with a rapid-iteration production system.”

Hsi-Chun Wang

Screened

Mid-level Data Scientist specializing in LLM development and scalable ML pipelines

Remote4y exp

“Built and deployed production LLM pipelines for evidence-based scoring in two domains: biomedical literature mining (scoring ~2700 drug compounds vs gene targets/mechanisms) and long-horizon news analytics (35 years of Chinese articles). Emphasizes reliability at scale (retries/checkpointing/validation), rigorous empirical model benchmarking (GPT-4o/mini/5), and translating results into stakeholder-friendly visual narratives.”

Ivan Pavkovic

Screened

Senior Paid Ads Specialist specializing in multi-platform performance marketing

Remote9y exp

“Performance marketer focused on e-commerce growth, managing $120K/month in spend across Google and Meta with reported 5x+ ROAS. Emphasizes full-funnel structure and creative iteration (copy, hooks, UGC) in collaboration with in-house creative teams, and prioritizes client reporting around sales/profit outcomes.”

Vikram Kini

Screened

Mid-Level Full-Stack Engineer specializing in React, TypeScript, and microservices

3y exp

“Built and productionized an AI agent-based in-app assistant at ISAFE to guide users through document workflows, piloting with a partner school district and then rolling out across districts. Combines hands-on LLM/agent debugging (logs, fallback rates, state/context tracking) with strong technical demos and sales enablement through live workflows and pilot programs (e.g., Osceola School District).”

Akshay Danthi

Screened

Senior AI Engineer specializing in production GenAI systems

San Francisco, CA8y exp

“AI engineer who has shipped production LLM systems end-to-end, including a natural-language-to-SQL analytics copilot for career advisors that achieved ~95% query success through schema grounding, access controls, and automated regression testing with golden queries. Also builds LangGraph-orchestrated multi-step agents (resume analysis, recommendations) and RAG pipelines (PDF ingestion + FAISS) and partners closely with non-technical users to drive adoption and trust.”

Dylan Zhu

Screened

Mid-level Machine Learning Engineer specializing in computer vision and generative AI

Hoboken, NJ7y exp

“Built and deployed an LLM/RAG system that uses differential privacy and distributional similarity checks to transform private data into a non-sensitive knowledge base while preserving utility. Also has experience demonstrating adversarial ML concepts (FGSM) to non-technical audiences by focusing on observable model behavior rather than implementation details.”

“Built and shipped LLM-powered agents including a production RAG research assistant that cut research lookup time from ~20 minutes to ~10–20 seconds using caching, retrieval thresholds, and citation-enforced grounded answers. Also designed multi-step, tool-calling workflows with stateful critique/revision loops and pragmatic monitoring (retry/schema-failure/low-confidence signals) plus normalization/validation layers for messy notes/spreadsheet-style data.”

“Cloud-focused platform/infrastructure engineer centered on AWS and Kubernetes, with hands-on experience building EKS environments via Terraform/Terragrunt, bootstrapping clusters with Cilium and ArgoCD, and integrating persistent storage and backup tooling like EFS/EBS CSI and Velero. While no longer focused on on-prem or hybrid operations, they also bring prior VMware/Hyper-V and migration-to-AWS experience, making them strongest in modern cloud platform engineering roles.”

“Builder-minded founder who co-started Renew-IQ, an insurtech company that landed successful pilots with major insurance brokerages and wholesalers without raising capital. Demonstrated practical enterprise product judgment by overcoming adoption challenges through integration with required compliant systems, improving user satisfaction, communication, and efficiency.”

Kavyashree Sudhakar

Screened

Junior Business Analyst specializing in operations and banking workflows

Tempe, AZ2y exp

“Entry-level data/business analytics candidate with hands-on experience building SQL and Python workflows to clean fragmented subcontractor data, generate risk scores, and feed Power BI dashboards. Also demonstrated strong operational analytics impact at Amazon by defining and operationalizing process-quality metrics that reduced CPO rate from roughly 10% to 0.6%.”

shivapriya pillalamarri

Screened

Mid-level AI/ML Engineer specializing in financial analytics and production ML systems

Boston, MA4y exp

“Analytics candidate with experience in financial transaction and fraud detection projects, combining SQL data preparation, Python-based automation, and dashboarding. They have owned projects from stakeholder alignment and metric definition through rollout, with emphasis on reducing false positives, improving operational efficiency, and making analytics outputs easy for business teams to adopt.”

“Analytics professional at Santander Bank with hands-on experience building SQL and Python workflows for transaction reporting, reconciliation, and monitoring across messy multi-source financial data. They combine strong data validation and exception-handling practices with stakeholder-friendly dashboards, and also bring digital analytics experience from a Google Analytics UI optimization project focused on funnel drop-off and engagement.”

Priyanshi Sharma

Screened

Mid-level Software Engineer specializing in FinTech full-stack and backend systems

Parsippany, NJ4y exp

“Built and productionized a GenAI prompt-engineering solution to retrieve prevailing wages based on job/location selections, emphasizing accuracy through stricter prompt templates and validation. Hands-on in real-time production debugging using Splunk (callback tracing, verbose logging, header inspection) and experienced running developer-facing demos/workshops that helped drive marketplace API adoption.”

Mahima Baddur

Screened

Mid-level Business Analyst specializing in data analytics and enterprise operations

5y exp

“Business/data analyst with Johnson & Johnson supply chain experience, focused on turning messy SAP, legacy, and Excel data into validated reporting datasets and Power BI dashboards. Stands out for combining SQL and Python automation with strong KPI design around inventory planning, inventory turnover, and demand analysis in a complex enterprise environment.”

“Startup-oriented product/technology leader targeting CTO roles, with experience evaluating and scoping high-impact product expansions. At Crelate, helped assess and shape a contract timekeeping/invoicing initiative that expanded TAM by hundreds of millions and increased ACV 2-3x, contributing to successful market traction and the company’s path to Series C.”

“Analytics professional at TIAA with hands-on experience combining SQL, Python, and statistical modeling to unify complex marketing, product, finance, and customer datasets. Has worked on advisor-tool adoption analysis, 10-year wealth diagnostics, forecasting, cohort analysis, and escalation-risk modeling, with findings used by marketing and contact-center stakeholders.”

“Built a production LLM-powered diagnostic agent at Supermicro that automated triage of NVIDIA H100/H200 GPU cluster failures by parsing BMC/Redfish logs and recommending fixes from historical RMA data. Their work combined agent architecture, reliability engineering, and backend optimization, delivering a 30% reduction in resolution time and 50% lower database load.”

“Analytics professional with healthcare and operations experience who turns messy enterprise data from platforms like Teradata, GCP, SQL Server, and Snowflake into trusted reporting layers and reproducible analysis workflows. They combine SQL, Python, PySpark, Power BI, and Tableau to improve reporting accuracy and performance, including a 30% dashboard refresh improvement and 20-25% accuracy gains in healthcare reporting.”

“Analytics professional with Dell experience unifying global online sales, web analytics, SAP, and planning data across 20+ countries into scalable reporting pipelines and Power BI dashboards. Stands out for combining deep SQL/ETL work with Python automation, KPI design, and experimentation—delivering measurable outcomes like 80% less manual effort, a 2% conversion lift worth millions, and faster business decision-making.”

Gnaneswar Markat

Screened

Mid-level Software Engineer specializing in cloud-native distributed systems

Charlotte, NC4y exp

“Full-stack engineer with Bank of America experience building and owning a customer portfolio dashboard end-to-end, from requirements through launch and ongoing iteration. They combine React/Spring Boot/PostgreSQL implementation with strong performance tuning, real-time data handling, and UX improvements, and cite adoption by roughly 12,000 active internal users.”

“Enterprise-minded builder who has owned complex, high-impact systems from discovery through stabilization, including a customer master data platform at AB InBev serving 2,000 sales reps across 13 countries. Also demonstrates strong AI product instincts, having built a first-place ReAct-style NYC property intelligence agent at IBM's AI Demystified Hackathon, while showing deep rigor in data quality, integrations, and production reliability.”

Pavan Punna

Screened

Mid-level AI/ML Engineer specializing in LLMs, MLOps, and healthcare-fintech AI

Dallas, TX5y exp

“Built and owned a production GPT-4 RAG assistant for clinical and enterprise query resolution, taking it from initial experiment to deployment, monitoring, and iterative improvement. Their work cut resolution time from 45 minutes to under 2 minutes, achieved roughly 95% accuracy, and scaled to thousands of additional monthly queries while emphasizing safety and trust in a sensitive clinical domain.”

“ML/AI engineer with production experience at S&P Global and Accenture, focused on regulated, enterprise-grade systems. Built end-to-end financial risk and credit default models with >90% precision and 12% fewer false positives, and is currently developing secure RAG pipelines on AWS SageMaker for enterprise insight extraction.”

“ML/AI engineer at PNC who has shipped enterprise-grade RAG and document intelligence systems for compliance and policy workflows. Stands out for combining LLM product thinking with production rigor—owning FastAPI/Kubernetes deployments, monitoring, evaluation, and human-feedback loops that drove measurable gains like 40% faster policy search and 30% faster compliance review.”