Vetted Microsoft Excel Professionals

“Education product leader with a strong track record building learner-facing engagement and AI features at Sophia, including an AI chat-based assessment, motivational messaging system, and course planning experience. Stands out for combining measurable product impact with thoughtful human-centered AI practices, academic integrity safeguards, and strong cross-functional leadership across product, engineering, academics, ops, legal, and PR.”

“Technical Product Owner with a technical background who led a net-new invoicing and reconciliation product across business stakeholders, architecture, and dependent teams, shipping close to target despite unexpected issues. Also brings a distinctive mentoring profile from tutoring and teaching in data analytics bootcamps, including hands-on support for learners with very low technical literacy.”

Kamilah Patterson

Screened ReferencesModerate rec.

Senior HR Business Partner specializing in talent strategy and workforce analytics

Brooklyn, New York11y exp

“HR Business Partner with GroupM experience supporting multiple mergers, building and transitioning Analytics/Programmatic/Account Management teams through hands-on job architecture, benchmarking, and performance management. Uses HR analytics (including an Excel-based retention model with visual reporting) and cross-functional partnership with IT to reduce disruption and improve retention during restructuring and major policy changes like return-to-office.”

“Sole founder of Bazaaro who built the company’s operations across product, hiring, GTM, finance, and investor relations—securing initial investment by effectively spanning multiple functions. Also drove a high-stakes operational turnaround at Ciena by process-mapping end-to-end workflows, correcting cost mis-modeling, and building Excel dashboards to recover $60K+ while improving margin visibility.”

“HR manager and lead recruiter with cross-border oversight (US, Canada, UK) and hands-on experience navigating region-specific employment law, benefits, and offboarding. Built product, analytics, and creative teams by designing structured hiring processes (panels, portfolio/presentation steps) and prioritizing candidate experience. Partnered with C-level leadership to migrate payroll/benefits from ADP Workforce Now to TriNet, coordinating IT/Finance and employee training for a smooth transition.”

“Former account manager/collector at Allied Account Services who ran 150–200 outbound calls/day (95% contact rate) and negotiated payment plans through an empathy-led, consultative approach. Also a solo e-commerce founder who launched a Shopify store and drove measurable growth (+55% traffic, +20% conversion, 120% monthly revenue growth in 3 months) and has been simulating SDR workflows in HubSpot with multi-channel outreach and automation/AI.”

“AI/ML Engineer who built a production RAG-based LLM system for insurance policy documents, turning thousands of messy PDFs into a searchable index using LangChain, Azure AI Search vectors, hybrid retrieval, and FastAPI. Strong focus on evaluation (MRR/precision@k/recall@k, REGAS) and performance optimization (vLLM), with prior clinical NLP experience using BERT-based NER validated on ground-truth datasets.”

“US Talent Acquisition/Recruiting Ops leader at Funbox (nearly 5 years) who owns end-to-end recruiting operations and ATS strategy, and who successfully pivoted into HR Ops during a 2022 slowdown (payroll, compliance, policies, reporting). Known for building operational rigor at scale—redesigned req approval/1:1 req-to-hire workflows, led Greenhouse→HiBob hiring module implementation in ~4 months, and executed a major hiring blitz (35→75 reqs; ~90% closed; 100+ referrals) across functions including engineering, product, sales, marketing, and frontline support.”

“University hackathon finalist (2nd place) who built CareerSpark, a production-style multi-agent career guidance app in 24 hours using a hierarchical debate architecture with a moderator/judge agent. Has startup internship experience at LiveSpheres AI using LangChain for multi-LLM orchestration, and demonstrates a structured approach to testing/evaluation (golden sets, integration sims, latency/accuracy KPIs) plus strong non-technical stakeholder communication.”

“Recent J&J intern who built a conversational RAG agent and led a shift from a monolithic model to a modular RAG workflow, cutting response time from several days to under a second by tackling data fragmentation, context retention, and embedding/latency optimization. Also worked on a large (7B-parameter) multimodal VQA pipeline for healthcare research and stays current via NeurIPS/ICLR and open-source contributions.”

“Data/ML practitioner with experience at Airtel and Lincoln Financial delivering measurable business outcomes: improved retention 15% via NLP sentiment analysis and cut response time ~25% using sentence-BERT + FAISS semantic linking. Strong in data quality/identity resolution (SQL + fuzzy matching) and in building production-grade Python workflows orchestrated with Airflow/AWS Glue, including validation and dashboard integration in Power BI.”

“AI/ML engineer who has deployed transformer-based NLP systems to production via Python REST APIs and Kubernetes on AWS/Azure, with a strong focus on latency optimization (p95), reliability, and scalable orchestration. Demonstrates pragmatic model tradeoff decision-making and strong stakeholder collaboration—improving adoption by making outputs more actionable with summaries, extracted fields, and confidence indicators.”

“Paid media performance marketer with hands-on ownership of high-spend ($100K+/month) display and online video campaigns in The Trade Desk, optimizing to CPA and VCR. Drove measurable improvements (20% CPA reduction, 15% VCR lift) using audience refinement, inventory curation, and creative optimization, and applies incrementality/marginal ROAS thinking to allocate spend across Google, Meta, and TikTok.”

“Data/QA-focused professional with experience at Lonza and Jio Platforms, owning end-to-end data reliability work for QC forecasting (SAP/LIMS) and driving root-cause/corrective actions for recurring environment configuration issues. Strong in SQL-based data standardization/validation, requirements tightening for API consistency, and coordinating multi-workstream delivery using Jira/Azure DevOps.”

“Data engineer in a banking context who has owned end-to-end Azure lakehouse pipelines ingesting financial/vendor data from APIs, Azure SQL, and flat files into Databricks/Delta (bronze-silver-gold). Emphasizes production reliability via schema-drift validation, data quality controls, monitoring/alerting, retries/checkpointing, and Spark/Delta performance tuning, with outputs served to BI/reporting teams (e.g., Tableau).”

Sanveed Adnan Qureshi

Screened

Senior Marketing Analytics & Operations Analyst specializing in performance marketing and BI

Albert Lea, MN4y exp

“Paid media/demand gen marketer who owned a $50K/month multi-brand budget (five business units) across Google Ads and LinkedIn Ads. Ran structured A/B tests and made fast budget reallocations based on benchmarks (CTR/CPL/lead quality), and diagnoses performance declines via funnel and saturation analysis (frequency/overlap) to stabilize CPAs and restore volume.”

Neus Tosi

Screened

Director-level Talent Acquisition & Development leader in beauty and pharmaceuticals

New York, NY9y exp

“Recruiting leader with experience managing teams of 2–5 and driving end-to-end recruiting process improvements, including SOP standardization, ATS implementations (Taleo/Paylocity), and data-driven reporting. Has led confidential executive searches (VP level) and partnered closely with HRBPs on strategic, high-volume initiatives such as building a global IT service center in Argentina (Boehringer Ingelheim).”

Amrita Mukherjee

Screened

Senior Talent Acquisition Manager specializing in executive search and account management

East Brunswick, NJ16y exp

“Staffing leader who has managed a team of 7 recruiters and delivered rapid, multi-location hiring across both direct and contract placements. Partners closely with client-side HRBPs and C-suite stakeholders, including handling contract negotiations, and has improved hiring outcomes in challenging geographies through relocation and sign-on incentive strategies.”

reza Hosseini

Screened

Senior Growth Marketing Manager specializing in B2B SaaS, AI automation, and performance growth

Los Angeles, CA14y exp

“Growth/performance creative lead with experience running high-velocity multivariate creative testing for an AI SaaS product at HTN Corporation across Meta, LinkedIn, TikTok, and YouTube. Built a modular creative system (Canva/Figma) plus automated Notion/Zapier performance tracking to ship 10–15 variants/week, cutting production time ~40% while improving outcomes (33% lower CPA, 2.6× ROAS).”

Erik Moyer

Screened

Director-level Data Science & Analytics Leader specializing in cloud data platforms and AI/ML

Dallas, TX13y exp

“Candidate states they are very familiar with the venture capital/studio/accelerator landscape and expresses strong willingness to pursue entrepreneurship "at all costs," but did not provide details on a current startup, business plan, fundraising, or prior accelerator/VC involvement during the interview.”

srilekha pothula

Screened

Mid-level Data Engineer specializing in cloud data pipelines for healthcare and financial services

Bloomfield, CT4y exp

“Data engineer with ~4 years of experience (Cigna) building and operating Azure Data Factory pipelines for healthcare claims/member/provider data at 2–3M records/day. Emphasizes reliability and downstream safety via schema/data-quality validation, quarantine workflows, idempotent processing, and backfills; also improved runtime ~20% through SQL optimization and served curated datasets through versioned views and well-documented, analyst-friendly interfaces.”

“Data Engineer (TCS) who owned an end-to-end CRM analytics pipeline for Bayer’s eSalesWeb integration, ingesting from Salesforce APIs/databases/S3 and serving analytics-ready datasets via PostgreSQL/S3 for Tableau. Drove measurable outcomes: ~60% reduction in manual data-quality effort, ~30% lower latency through SQL optimization, and ~35% improved stability via monitoring, retries, and idempotent processing.”