Pre-screened and vetted in Pennsylvania.
Staff Data Analytics Lead / Data Scientist specializing in manufacturing process control
“Intel veteran who applied multiple linear regression and time-series drift analysis to semiconductor lithography overlay/metrology data, feeding model outputs into automated process control. Comfortable working across Python, VBA, and JMP/JSL, with a pragmatic approach to validation (RMSE + trend visualization) and data quality via close coordination with measurement/metrology teams.”
Mid-level Data Scientist specializing in NLP, MLOps, and semiconductor manufacturing analytics
Mid-level Data Scientist specializing in anomaly detection and production ML
“Interned at Backblaze building production AI systems for incident response and security operations, including an internal LLM-powered incident triage assistant that used Snowflake + RAG over historical tickets/postmortems and delivered results via Slack and a web UI. Emphasizes reliability (PII filtering, grounding, schema validation, fallbacks) and rigorous evaluation/observability (offline replay, partial rollouts, time-to-first-action metrics, Prometheus/Grafana).”
Mid-level Data Scientist specializing in business intelligence and machine learning
“Internship experience building a production LLM-powered podcast operations agent that automated lead intake (HubSpot), guest research, scheduling (Calendly), meeting-summary evaluation (Gemini), and human approval via Slack bot—while retaining rejected candidates for future outreach. Also contributed to ideation of a multi-agent orchestration framework with parsing and task routing, and emphasized reliability via structured prompts, HITL feedback, and prompt-based test sets.”
Senior Data Analyst specializing in audit analytics, automation, and financial data platforms
“Full-stack engineer with strong Next.js App Router + TypeScript experience who built and owned a production internal analytics dashboard end-to-end, including server-component data fetching, route handlers for secure proxying, and post-launch monitoring/caching fixes. Also designed Postgres data models and performance-tuned analytics queries, and built reliable BullMQ/Redis-based order-fulfillment workflows with idempotency, retries, and compensating refunds—comfortable operating with high ownership in early-stage teams.”
Executive Data & Analytics Leader specializing in enterprise platforms, AI/ML, and healthcare
Senior Data Engineer specializing in cloud lakehouse platforms and streaming analytics
Senior Data Scientist specializing in healthcare analytics and scalable ML pipelines
Mid-level Business Analyst specializing in Healthcare IT and Banking operations
“Cross-functional operator who regularly leads globally distributed work and acts as a bridge between product, UX, and analytics. Has driven reporting/dashboard and workflow automation initiatives with senior leadership, using data-backed communication and quick wins to improve adoption and efficiency.”
Mid-level AI/ML Engineer specializing in Generative AI and production ML systems
“Built and deployed a production SecureAIChatBot (RAG-based) for secure internal information retrieval, using embeddings/vector search, GPT models, monitoring, and safety filters. Focused on real-world production challenges like latency and output consistency, applying caching, retrieval scoping, smaller models, and controlled prompting, and used LangChain to orchestrate the end-to-end workflow.”
Mid-level Data Scientist specializing in NLP, MLOps, and Generative AI
Mid-level Data Analyst specializing in financial and healthcare analytics
Mid-level Data Scientist specializing in ML, NLP, and GenAI (RAG)
Mid-level Paid Media Analyst specializing in performance marketing for healthcare and pharma
Mid-level Data Scientist specializing in credit risk, fraud detection, and ESG analytics
“AI/LLM practitioner who has deployed production chatbots across e-commerce, HRMS, and real estate, focusing on retrieval-first workflows for factual tasks like product and property search. Optimized intent understanding and significantly improved latency by using lightweight embeddings and tuning the inference pipeline on Groq (Llama 3.3), while applying modular orchestration and measurable production evaluation.”
Mid-level Data Engineer specializing in AI/ML, RAG systems, and cloud data pipelines
“Built a production lead-generation system using AI agents that researches the internet for relevant leads and integrates RAG-based contact enrichment/shortlisting aligned to existing CRM data, enabling sales reps to focus more on selling. Also has hands-on AWS data orchestration experience (Glue, Step Functions) moving raw data into Redshift and evaluates agent performance with human-in-the-loop plus BLEU/perplexity metrics.”
Mid-level Data Scientist specializing in ML, predictive analytics, and automation
Mid-level Sourcing & Supply Chain Analyst specializing in procurement analytics and cost reduction
Senior Autonomy & GNC Researcher specializing in state estimation, sensor fusion, and control