Vetted Statistical Analysis Professionals

“Backend engineer who built and evolved Python/FastAPI services (including AWS-deployed ML prediction APIs) for real-time profitability and risk insights at TenXengage. Emphasizes pragmatic architecture, strong validation/observability, and secure access controls (RBAC + row-level filtering), and has led safe migrations via parallel runs and incremental rollouts; reports ~20% forecasting accuracy improvement.”

“Analytics-focused candidate with hands-on project experience in SQL data preparation and Python-based churn modeling. They demonstrated a practical approach to turning messy multi-source data into reporting tables, validating data quality rigorously, and translating churn insights into targeted retention strategies.”

“Built and deployed an LLM product called "Content Craft" combining BART-based summarization with a RAG Q&A chatbot using LangChain, embeddings, and a vector database. Has hands-on MLOps experience containerizing and serving models with FastAPI and running them on Kubernetes with monitoring, self-healing, and autoscaling, and has practical experience reducing hallucinations through structured prompting.”

“Data/ML practitioner who has built a production RAG-based knowledge assistant integrated into Microsoft 365/internal dashboards to help employees query internal documents in plain English. Experienced orchestrating and hardening ETL pipelines with Airflow and Azure Data Factory (validation, retries, monitoring) and running end-to-end model evaluation and production performance tracking via Power BI.”

Siddharth Ranjan

Screened

Mid AI/ML Engineer specializing in LLMs, RAG, and cloud AI systems

Maryland, USA4y exp

“Built an AI-powered job matching platform end to end using AWS, Gemini, FastAPI, TypeScript, embeddings, and vector search. The standout result was automating manual matching workflows and scaling resume processing to roughly 2,000 resumes per minute while monitoring quality with F1 score and latency metrics.”

“Backend engineer specializing in event-driven/serverless systems and Python/FastAPI APIs. Built a scalable PDF-to-structured-data pipeline on AWS (S3, Lambda, Step Functions, Textract, DynamoDB, SNS) with strong observability (p50/p90/p99) and reliability patterns (idempotency, retries/DLQs), and has led zero-downtime migrations using feature flags, dual writes, and incremental rollouts.”

“LLM engineer/data analyst who built a production RAG QA assistant over the Jurafsky & Martin NLP textbook to reduce hallucinations and provide explainable, source-grounded answers. Experienced with LangChain/LangGraph orchestration, retrieval optimization (embeddings, vector DBs, caching), and rigorous evaluation/monitoring (Retrieval@K, A/B tests, telemetry/drift). Previously communicated analytics insights to non-technical stakeholders at GS Analytics using Power BI and simplified reporting.”

Visswanath Baskaran

Screened

Mid-level Data Analyst specializing in BI, ETL, and forecasting

Tampa, FL4y exp

“Analytics professional with hands-on experience at Charge Dock building SQL- and Power BI-based operational reporting for SLA compliance, uptime, and incident management. Also developed a reproducible Python demand forecasting workflow using Pandas and Statsmodels to support inventory planning, showing a blend of BI, data engineering, and forecasting capability.”

MUNI CHARAN SINGAMALA

Screened

Mid-level Data Analyst/Data Engineer specializing in SQL, ETL pipelines, and BI dashboards

Florida, USA4y exp

“Built and supported a production analytics backend (Python, PostgreSQL/Teradata, Airflow) powering KPI/reporting dashboards, and resolved peak-time latency/timeouts through systematic SQL tuning (EXPLAIN ANALYZE, indexing, query rewrites, pre-aggregations). Also shipped an applied AI-style feature that generates plain-language report summaries from pre-computed metrics with validation, monitoring, and fallback to manual review.”

“AI/backend engineer who independently built and operated an agentic telecom analytics system end-to-end, using LangGraph and Claude to turn natural language into safe SQL in a regulated environment. He combines startup-speed execution with compliance-minded rigor, citing 95%+ NL-to-SQL accuracy, a 30-minute-to-2-minute workflow improvement, and zero-findings support across three regulatory audit cycles.”

“Sales professional at AutoSherpa who partners closely with product/engineering to resolve CRM data-sync issues affecting pipeline accuracy and sensitive customer data handling. Experienced running multiple customer onboardings in parallel using structured tracking (CRM/project boards), early risk logging, and weekly stakeholder syncs; targeting $100k base and open to equity.”

“Marketing and product-focused analytics candidate with hands-on experience turning messy large-scale data from Hadoop/HDFS, Azure Data Lake, and transaction systems into validated reporting tables. They combine SQL and Python automation with strong metric design, cohort/retention analysis, and stakeholder-friendly dashboards, including a reported 30% query performance improvement and weekly reporting automation.”

Alexander Home

Screened

Mid-level investment analyst specializing in portfolio analysis and financial modeling

Oregon, USA4y exp

“Sales-focused candidate with high-volume outbound experience targeting founders and operators, primarily through LinkedIn, email, and cold calling. They report operating at 200 calls per day, booking 10 meetings per week, and contributing to $5M per quarter, with a founder-sourced opportunity specifically cited as bringing in $5M of business. They emphasize tailored messaging, trust-based relationship building, and disciplined CRM pipeline management in fast-paced environments.”

“Built and deployed production LLM applications including a natural-language-to-read-only-SQL system focused on ambiguity handling and query safety (schema whitelisting, intent validation, confidence checks, deterministic execution). Experienced with LangChain-based, modular agent orchestration and RAG document QA for large PDFs, with a metrics-driven testing/evaluation approach and cross-functional delivery with marketing on an AI content recommendation/search tool.”

“Lifecycle/CRM marketer from Lid Vizion who led behavior-segmented onboarding/reactivation email programs, delivering a 26% lift in email engagement. Experienced running A/B tests (subject lines, CTAs, send times) and coordinating cross-functionally across creative/product/dev to align influencer, blog, and email messaging—cutting go-to-market time by 20%.”

Riya Stanly

Screened

Intern Data Scientist specializing in machine learning, NLP, and LLM fine-tuning

2y exp

“Built a production-style AI meeting summarization and action-item extraction system (Azure Speech-to-Text + transformer summarization/NER) exposed via a Flask REST API, with explicit guardrails to prevent hallucinated tasks. Strong focus on reliability: modular agent/workflow design, precision-first evaluation with human-validated golden notes, and practical orchestration patterns (tool-augmented agents; ready to scale into Airflow/LangGraph/Prefect).”

“Built and deployed a Unity-based, NSF-funded medical interaction system for the University of Houston MRI Lab, combining speech recognition, LLaMA-based function calling, and real-time simulation controls. Particularly strong in taking experimental AI systems from discovery through stabilization, with measurable impact including roughly 50% faster task completion than traditional point-and-click workflows.”

“Full-stack and AI product engineer with strong accessibility and voice-interface experience in senior living, building systems for older adults where trust and usability are critical. Has shipped React/TypeScript and .NET MAUI products, productionized Azure OpenAI features, built RAG-based research tools, and improved both product outcomes and technical performance with measurable impact.”

“Robotics software candidate who built a Q-learning smart delivery drone navigation system, focusing on 2D path planning with dynamic obstacle avoidance using reward shaping and real-time sensor feedback. Actively learning ROS 2 by building Python simulation projects with publisher/subscriber patterns and has experience coordinating multi-agent drone simulations via message passing.”