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Vetted Power BI Professionals

Pre-screened and vetted.

CJ

Clidner Joseph

Screened ReferencesStrong rec.

Senior Talent Acquisition & Recruiting Operations Partner specializing in hiring analytics

New York, NY6y exp
Omnicom Media GroupBaruch College

Recruiting leader in the agency/media space (Omnicom/Hearts & Science and WPP Media) who manages a small recruiter pod and builds operational systems to improve hiring outcomes. Known for process standardization and change management (Greenhouse templates, SLAs, automation) and for measurable stakeholder impact—e.g., cutting hiring manager response lag to 48 hours and partnering with a CFO to prioritize/stagger hiring based on capacity and budget.

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PC

Patricia Ceron

Screened ReferencesStrong rec.

Senior Growth & Demand Gen Marketer specializing in B2B SaaS partnerships and GTM

Vancouver, BC, Canada20y exp
Dancing Line ProductionsJTL University

Growth/partnerships leader with experience across Hootsuite, SMART Technologies, and Spinify, building partner ecosystems and GTM programs tied directly to pipeline and revenue. Notably created agency partnerships that drove 21% of total revenue and ran a data-backed self-serve SMB experiment that produced an 18.4% lift in conversations.

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NC

Mid-level Supply Chain Planner/Buyer specializing in sourcing, MRP, and analytics

Boston, MA4y exp
ASMPTNortheastern University

Supply chain/sourcing professional focused on semiconductor tooling NPI ramp-ups, owning vendor selection through production and delivery. Demonstrates strong cost and trade-risk mitigation (e.g., avoided 25% Section 301 tariff via HTS/landed-cost analysis) and measurable supplier performance turnarounds (OTD improved to 95%) using SAP MRP, shortage analysis, and structured supplier governance.

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SD

Sanya Dod

Screened

Junior Software Engineer specializing in AI/ML and verification

West Lafayette, IN2y exp
WISE Lab, Purdue UniversityPurdue University

Embedded/real-time robotics-style engineer with hands-on STM32 development, sensor integration, and low-level drivers, focused on deterministic control behavior. Demonstrated systematic debugging of jitter/latency by instrumenting the sensing-to-actuation pipeline and eliminating blocking via interrupts, hardware timers, and DMA; also designs asynchronous, message-based interfaces for distributed real-time components. Familiar with ROS/ROS2 concepts (nodes/topics/callbacks) though not yet deployed a full production ROS system.

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NK

NEHA KOLAN

Screened

Mid-Level Software Engineer specializing in microservices and cloud data pipelines

Texas, USA4y exp
CignaUniversity of North Texas

Full-stack engineer with end-to-end ownership across React/TypeScript frontends, Spring Boot/Node microservices, and production ops on Docker/Kubernetes and AWS (ECS/CloudWatch). Built real-time healthcare eligibility and analytics systems at Cigna and an early-stage seller onboarding platform at Flipkart, driving measurable performance gains (35–40% latency/throughput improvements) through event-driven Kafka pipelines, Redis caching, and strong reliability/observability practices.

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JS

Jitesh Sharma

Screened

Mid-level Growth Marketing Manager specializing in performance creative and marketing analytics

Mumbai, India3y exp
MirumUniversity of Texas at Austin

Paid social creative lead with experience across major consumer brands (Duracell, Amazon Groceries, Puma) and Gen Z-focused retail, owning end-to-end creative strategy from concept/briefing and UGC direction through QA and delivery. Known for contextual, seasonally-timed campaigns and performance-driven iteration (CPA/ROAS, funnel drop-offs), including a Duracell Meta campaign that reached 20M+ views and sustained engagement gains via creator feedback loops.

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PT

Principal Data Strategy & Data Management Leader specializing in enterprise governance and analytics

Woodstock, IL25y exp
Taylored ConsultingSouthern Illinois University

Operator/program leader with experience building operating models and execution cadences for data/analytics and energy data services across Entech, HealthEquity, and RealPage. Has launched an undefined energy data management service into regulated enterprise environments and driven cross-functional alignment via dashboards, SLAs, and OKRs—contributing to enterprise wins and a successful company sale.

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CN

Mid-Level Software Engineer specializing in Java, Spring Boot, and AWS

USA4y exp
Progress SolutionsUniversity of Michigan

Built and deployed a production credit card fraud detection platform that scores transactions in real time using TensorFlow/scikit-learn models exposed via a Spring Boot REST API, with strict SLAs, fallback to legacy rules, and Splunk-based monitoring/drift tracking. Also has enterprise orchestration experience with TIBCO BusinessWorks (BW 6.6/BWCE), coordinating REST/SOAP services and JMS messaging (TIBCO EMS) with robust error handling and compensation logic.

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AR

Mid-level AI Engineer specializing in GenAI, NLP, and MLOps

Remote, USA3y exp
PayPalUniversity of Central Missouri

LLM/agentic-systems engineer with PayPal experience hardening an LLM-powered fraud support assistant from prototype to production, focusing on low-latency distributed architecture, rigorous evaluation/testing, and security/compliance. Comfortable in customer-facing and GTM contexts—runs technical demos/workshops, builds tailored pilots, and aligns sales/CS with engineering to close deals and drive adoption.

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SM

Shravya M

Screened

Senior AI/ML Engineer specializing in NLP, LLMs, and MLOps

Texas, USA6y exp
CVS HealthUniversity of North Texas

LLM/agent workflow engineer with healthcare experience (CVS/CBS Health) who built and deployed a production call-insights platform using Azure OpenAI + LangChain/LangGraph, including sentiment and compliance checks. Demonstrates deep HIPAA/PHI handling (tenant-contained processing, redaction, RBAC/encryption/audit logging) and production rigor (testing, eval sets, validation/retries, autoscaling) to scale to thousands of transcripts.

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NN

Mid-level AI/ML Engineer specializing in Generative AI and MLOps

4y exp
WalgreensUniversity of North Texas

Built and deployed a production Retrieval-Augmented Generation (RAG) platform in a healthcare setting to automate clinical documentation review and summarization, targeting near-real-time, explainable outputs. Emphasizes grounded generation to reduce hallucinations, latency optimizations (chunking/embedding reuse), and PHI-safe workflows with access controls, plus strong orchestration experience using Apache Airflow.

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NG

Mid-level AI/ML Engineer specializing in Generative AI, NLP, and Computer Vision

Grand Rapids, MI4y exp
IntuitGrand Valley State University

Built an LLM-powered learning assistant (EduQuizPro/EduCrest Pro) that uses RAG over URLs and PDFs to generate quizzes, notes, and explanations for students/professors. Emphasizes production robustness—implemented dependency fallbacks (FAISS/Sentence Transformers/Gradio), CLI-safe mode, and NumPy-based indexing—along with a custom orchestration layer to keep multi-step AI workflows reliable.

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SK

Mid-level Data Scientist / AI-ML Engineer specializing in Generative AI and LLM applications

Dallas, TX5y exp
Baylor Scott & WhiteUniversity of North Texas

Built a production GenAI-powered analytics assistant to reduce reliance on data analysts by enabling natural-language Q&A over Databricks/Power BI dashboards, backed by vector search (Pinecone/Milvus) and a Neo4j knowledge graph, including multimodal support via OpenAI Vision. Demonstrates strong real-world LLM reliability engineering with strict RAG, LangGraph multi-step verification, and Guardrails/custom validators, plus broad orchestration and production monitoring experience (Airflow, ADF, Step Functions, Kubernetes, Prometheus/CloudWatch).

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MM

Madhu Moutam

Screened

Mid-level Supply Chain Analyst specializing in logistics optimization and planning analytics

USA (Remote)4y exp
MaerskConcordia University

Supply chain/procurement professional (Maersk) who leads end-to-end freight sourcing initiatives using heavy analytics (SAP/SQL/Python/Excel) to drive measurable savings. Known for automating sourcing workflows (60% faster bid evaluation) and building Power BI dashboards to monitor contract compliance and supplier performance post-implementation.

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SR

Mid-level AI/ML Engineer specializing in deep learning, NLP/LLMs, and MLOps

MA, USA6y exp
Flatiron HealthClark University

Built and shipped a real-time oncology risk prediction system used by doctors during patient visits, trained on clinical data in AWS SageMaker and deployed via FastAPI with sub-second responses. Emphasizes clinician-trust features (SHAP explainability, validation checks) and HIPAA-compliant controls (encryption, RBAC, audit logging), plus Kubernetes-based production operations with autoscaling, monitoring, and drift/retraining workflows; collaborated closely with oncologists at Flatiron Health.

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AK

Ayaan Katoch

Screened

Junior Business & Operations Analyst specializing in energy and e-commerce growth

New Delhi, India2y exp
SAEL Industries Ltd.York University

Sales/business development candidate with hands-on outbound experience targeting Amazon FBA sellers, combining cold calling and LinkedIn outreach with event-based lead generation at seller conferences. Uses AI tools (Notion, Gemini, ChatGPT) and company research to tailor scripts and messaging based on a prospect’s growth stage and needs, with a focus on SMEs seeking Amazon reimbursement services.

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SB

Silpa Bhavani

Screened

Mid-level Full-Stack Java Developer specializing in cloud-native microservices

Oakland, CA5y exp
BlockLamar University

Software engineer with strong compliance-domain experience who built a customer-facing compliance and reporting dashboard using React/TypeScript with Spring Boot microservices. Demonstrates mature production engineering practices—contract-first APIs, event-driven architecture (Kafka/RabbitMQ), caching (Redis), and robust CI/CD + observability (Prometheus/Grafana/ELK)—and also created a Python-based audit automation tool adopted into the standard release process.

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TK

Mid-level AI/ML Engineer specializing in Generative AI, RAG, and Conversational AI

3y exp
AetnaIndiana Tech

Built a production RAG-based GenAI copilot backend at Aetna using Python/FastAPI, GPT-4, LangChain, and Azure AI Search, deployed on AKS with Prometheus/Grafana observability. Owned the system end-to-end (ingestion through deployment) and improved peak-time reliability by addressing vector search and embedding bottlenecks with Redis caching, index optimization, and async processing, plus added anti-hallucination guardrails via retrieval confidence thresholds.

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CM

Chris Marcus

Screened

Executive CTO & AI Architect specializing in regulated SaaS (InsurTech/Healthcare/FinTech)

Remote15y exp
agentCanvas.aiUniversity of Texas at Austin

Insurance-tech CTO and repeat founder with 10+ years in insurance startups; was employee #4/CTO at Polly (formerly DealerPolicy) and helped scale it from a PowerPoint to 250 employees while raising $180M+. Currently building and selling AgentCanvas.ai—an extensible AI accelerator platform for large insurance agencies—after coding the product end-to-end and now running demos/POCs with prospective buyers.

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ML

Maurice Lange

Screened

Executive Technology & Data Leader specializing in cloud platforms, AI/ML, and enterprise data

Tampa, FL35y exp
HigherEchelonRotterdam School of Management, Erasmus University

Former PwC Director with hands-on early-stage venture experience (e.g., BridgeLights, a big-data analytics concept for early fintech) spanning concept creation, platform architecture, and go-to-market experimentation. Strong focus on building scalable, modular data platforms with rigorous governance/compliance (data lineage, quality controls) and supporting technical diligence in investor-aligned environments.

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DB

Mid-level AI/ML Engineer specializing in LLMs, RAG, and MLOps on AWS

TX, USA5y exp
BlackRockTexas A&M University-Kingsville

AI engineer who built a production RAG-based internal analyst tool at BlackRock, fine-tuning an LLM on proprietary financial data and adding four layers of guardrails (input/retrieval/generation/output) to improve grounding and reduce hallucinations. Implemented a LangChain-based multi-agent orchestration (7 major agents) deployed on AWS ECS, with reliability measured via internal human evaluation, LLM-as-judge, and RLHF/drift monitoring.

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MK

Mahima Korad

Screened

Mid-level Supply Chain Analyst specializing in planning, procurement, and distribution operations

Santa Clara, CA5y exp
HD SupplySan José State University

Sourcing/procurement professional with Accenture experience supporting telecom infrastructure expansion, owning RFQs through delivery and managing 12+ vendors. Known for strong supplier performance management (scorecards, KPIs, corrective actions) delivering ~97% on-time material delivery while cutting expedited freight 13% and avoiding ~AUD 500K in delay costs; also brings supplier onboarding and capability/capacity assessment experience from Nestlé and Accenture.

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GB

Ganesh Bandi

Screened

Mid-level AI Engineer specializing in LLMs, RAG, and MLOps

USA6y exp
Capital OneUniversity of North Texas

LLM engineer who has deployed production RAG systems for regulated document QA (PDFs/knowledge bases), emphasizing grounded answers with citations, RBAC, monitoring, and continuous feedback. Demonstrates deep practical expertise in retrieval quality (semantic chunking, hybrid BM25+embeddings, re-ranking), reliability (guardrails, deterministic workflows), and measurable evaluation (golden sets, log replay, A/B tests) while partnering closely with compliance/operations stakeholders.

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AS

Aayushi Singh

Screened

Intern AI/ML Engineer specializing in robotics and computer vision

Los Angeles, CA0y exp
BoltIOTUSC

Worked on Sophia the humanoid robot, building production animation pipelines and enhancing human-robot interaction via perception and behavior orchestration. Experienced in stabilizing noisy perception-driven state transitions and designing smooth, user-centered behavioral flows, collaborating closely with artists, animators, and experience designers to translate creative intent into measurable system behavior.

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