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I’m an Upwork Expert-Vetted Salesforce & HubSpot Partner and Consultant. An Analytics Professional with strong Operational and Technical skills. Working with a knowledgeable Consultant with a background in both Analytics and Business ensures that both your Technical and Operational needs are met, allowing your to focus on Strategy and Growth. With my expertise in Analytics and an MBA in Business, I bring valuable insights to my Clients on both their Systems and Operational needs. Backed by 11 Salesforce & 6 HubSpot Certifications and multiple implementations, I build best practice Solutions for my Clients. Together, we can build your ideal state and empower your Teams for success.

Most data consultancies fall into one of two camps: strategy firms that hand you a slide deck and walk away, or implementation shops that sit around waiting for you to tell them exactly what to build. Neither works if you're a mid-market company with zero to two data hires. At Data-Sleek, we own the full path from data strategy through AI enablement so you don't have to hire a team to do it well. You shouldn't have to hire a Head of Data just to start. My name is Franck Leveneur. 𝗜 𝗯𝗿𝗶𝗻𝗴 𝟯𝟬+ 𝘆𝗲𝗮𝗿𝘀 𝗼𝗳 𝗵𝗮𝗻𝗱𝘀-𝗼𝗻 𝗱𝗮𝘁𝗮𝗯𝗮𝘀𝗲 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 𝗲𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲. Since 2018, I've taught Data Management at the UCLA Anderson School of Management for the Master of Science in Business Analytics (MSBA) program. I founded Data-Sleek in 2020 as a boutique consulting firm built around this exact gap in the market. On Upwork, we've earned over $𝟓𝟎𝟎,𝟎𝟎𝟎 𝐚𝐜𝐫𝐨𝐬𝐬 𝟏𝟑𝟗 𝐜𝐨𝐦𝐩𝐥𝐞𝐭𝐞𝐝 𝐣𝐨𝐛𝐬. Clients consistently tag my work as "Committed to Quality," "Solution Oriented," and "Clear Communicator." When you work with me, you're not getting a junior freelancer learning on your dime; you're getting a 𝐛𝐚𝐭𝐭𝐥𝐞-𝐭𝐞𝐬𝐭𝐞𝐝 𝐯𝐞𝐭𝐞𝐫𝐚𝐧 who has built data ecosystems for high-growth companies like Numerade, Digital Asset Research, and Johns Hopkins, among 15+ others. ──────── 🚨𝐓𝐇𝐄 𝐏𝐑𝐎𝐁𝐋𝐄𝐌 𝐖𝐄 𝐒𝐎𝐋𝐕𝐄 Your company has data - a lot of it. But: 1. Your systems don't talk to each other (ERP, CRM, EHR, TMS - all siloed) or you don’t know where to start Comment end 2. KPI reporting takes too long, and nobody quite trusts the numbers 3. You want to use AI and predictive analytics, but your data isn't ready 4. You've tried BI tools. You still don't have real answers. This is not a tool problem. It's a foundation problem. And that's exactly what we fix. 🚀 𝐇𝐎𝐖 𝐖𝐄 𝐖𝐎𝐑𝐊 - 𝐓𝐇𝐄 𝐅𝐎𝐔𝐑-𝐏𝐈𝐋𝐋𝐀𝐑 𝐅𝐑𝐀𝐌𝐄𝐖𝐎𝐑𝐊 We guide clients through a structured data journey. You can engage at any stage: 1. Data Strategy (Discovery & Alignment, optional but recommended) Data inventories, AI readiness assessments, architecture design, and strategic roadmaps. 2. Data Centralization (Integration & Governance) Single source of truth via Snowflake, BigQuery, or Redshift connected through Fivetran and governed pipelines. 3. Data Transformation (Modeling & Preparation) dbt consulting, semantic layers, and ETL/ELT pipelines that model your data for analysts and AI. 4. Data Activation (Insights, Prediction & AI) BI, Tableau dashboards, predictive analytics, and ML wherein raw data turned into real business outcomes. DATA WAREHOUSE CONSULTING SERVICES Struggling with complex data warehousing projects can hinder your company’s ability to scale. Our data warehouse consulting services are tailored to address your business’s data needs. 🙅🏼‍♂️ 𝐃𝐀𝐓𝐀𝐁𝐀𝐒𝐄 𝐄𝐗𝐏𝐄𝐑𝐓𝐈𝐒𝐄 - 𝐓𝐇𝐄 𝐓𝐇𝐈𝐍𝐆 𝐌𝐎𝐒𝐓 𝐂𝐎𝐍𝐒𝐔𝐋𝐓𝐀𝐍𝐂𝐈𝐄𝐒 𝐂𝐀𝐍'𝐓 𝐃𝐎 Unlike modern data stack consultancies that only know cloud tools, we know how the underlying transactional systems actually work. I have 15+ years as a Senior MySQL DBA and deep expertise across: ➝ MySQL & AWS Aurora ➝ PostgreSQL ➝ ClickHouse ➝ MS SQL Server ➝ SingleStore Performance tuning, partitioning, replication, and scaling, not just dashboards on top of messy data. 🏭 𝐈𝐍𝐃𝐔𝐒𝐓𝐑𝐈𝐄𝐒 𝐖𝐄 𝐒𝐏𝐄𝐂𝐈𝐀𝐋𝐈𝐙𝐄 𝐈𝐍 ➔ Construction ➔ Healthcare ➔ Higher Education ➔ Insurance ➔ Transportation ➔ SaaS ➔ EdTech ➔ FinTech We have dedicated playbooks, industry-specific data models, and named case studies in each. If your company is in one of these five, we've already solved your problem before. 💯 𝐏𝐑𝐎𝐕𝐄𝐍 𝐑𝐄𝐒𝐔𝐋𝐓𝐒 🏆 Johns Hopkins (Higher Education): Data warehouse architecture consulting reduced reporting time by 40% and increased data accuracy by 35% within the first year. 🏆 Numerade (EdTech): Redesigned database schema and ETL processes - query times dropped from several minutes to sub-second, system outages eliminated, scaled to unlimited concurrent users, subscriber growth followed. 🏆 Digital Asset Research (FinTech/Crypto): Built a real-time ingestion pipeline handling 40 million rows daily (250M+ trades). Client expanded their client base by 600% and captured the largest market share in their category. 💡 𝐀𝐈 𝐑𝐄𝐀𝐃𝐈𝐍𝐄𝐒𝐒 𝐀𝐒𝐒𝐄𝐒𝐒𝐌𝐄𝐍𝐓 - 𝐓𝐇𝐄 𝐑𝐈𝐆𝐇𝐓 𝐖𝐀𝐘 𝐓𝐎 𝐒𝐓𝐀𝐑𝐓 𝐀𝐈 Most AI projects fail because the data foundation underneath them isn't ready; not because AI is hard. If you want predictive analytics, ML models, or intelligent automation, start here: → Fixed-fee engagement · 4-6 weeks · Clear deliverable: which AI use cases your data can support today, and the roadmap to support more. ──────── 🌱 𝐋𝐄𝐓'𝐒 𝐆𝐄𝐓 𝐒𝐓𝐀𝐑𝐓𝐄𝐃 We always start with a free initial consultation to scope the work properly before any engagement begins. Send a message - let's see if we're a fit!

I am a Statistical Consultant and MS Statistics student at UC Davis. I also received a B.S. in Applied Mathematics/Economics and a Minor in Business Analytics from the University of California, Riverside. 🏆 Elite Credibility: My coauthored research has been selected for presentation at premier national conferences, including: 1️⃣ 2025 Association for Public Policy Analysis & Management (APPAM), Seattle, Washington 2️⃣ 2025 Population Association of America (PAA), Washington, D.C. 📈 Specialized Statistical Services: I leverage R, Stata, and Python to solve complex causal and predictive problems: ✅ Descriptive Regression Analysis: Linear/nonlinear regression, probability modeling (LPM, logistic), ANOVA (One-Way, Two-way, Random / Fixed / Mixed Effects) ✅ Causal Inference: Difference-in-Differences (DiD), Instrumental Variables (IV), and Panel Data (Random / Fixed / Mixed Effects) ✅ Predictive Modeling: Machine Learning (Gradient Boosted Trees, Random Forest, KNN) ✅ Survey Methodology: Expert population weighting, clustering, and post-stratification ✅ Statistical Tests: A/B tests, T-tests, Chi-squared Tests, Hausman test, etc. Some Projects: 1️⃣ Github Website (with an interactive dashboard using PostgresSQL and Python, portfolio, and other webpages on reproducible research) 2️⃣ Regression Analysis of Airbnb prices in Mexico 3️⃣ Regression Analysis of H-1B sponsor rates by industry type and location In a year-long data analytics intern position, I: 1️⃣ Created and implemented a database into our center's initiative on analyzing academic technology usage. 2️⃣ Reached out to technology vendors of the university, requesting data extracts and communicating with them on the interpretation of data. 3️⃣ Streamlined data collection, and organized all data into a database that is still used at the center. 4️⃣ I cleaned and prepared several spreadsheets with hundreds of thousands of rows within Google Sheets, and provided key metrics through dashboards and reports in Google Looker Studio. 5️⃣ I connected this data and made it accessible through Slack. I reported on my progress through Slack, Asana, and Zoom meetings (disseminating findings through bi-weekly meetings). 6️⃣ I implemented data governance policies and facilitated meetings on data governance. 7️⃣ I wrote, recorded, and hosted trainings for my colleagues in Looker Studio. 8️⃣ Providing data-driven insights through story-telling. 🛠 Technical Toolkit: Languages: R, Python , SQL (PostgreSQL), Stata. Visualization: Plotly, ggplot, Looker Studio

I build marketing analytics and attribution systems that show exactly which campaigns, channels, and product behaviors drive revenue, so growth teams can scale what works and cut what doesn’t. With 5+ years as a Data Engineer and Analytics Consultant, I partner with marketing, product, RevOps, and executive teams to stitch together ad platforms, analytics tools, CRMs, and product event data into one consistent reporting layer across the full funnel from acquisition to retention. Focus areas Marketing & Attribution Analytics • Tools: GA4, Meta, Google Ads, TikTok, pixels, Meta Conversions API, Google Tag Manager, server-side tracking, BigQuery, Power BI, Looker • Techniques: UTM governance, click-ID stitching, session-to-order joins, multi-touch and last-touch attribution, campaign and creative analysis, custom funnel tracking • Outcome: Clear views of channel contribution, campaign efficiency, and customer acquisition performance Funnel, Pipeline & Conversion Analytics • Tools: GA4, CRM systems (HubSpot, GoHighLevel, PipeDrive, etc.), SQL, dbt, cloud warehouses, BI dashboards • Techniques: Funnel modeling from first touch to revenue, lead-to-opportunity tracking, conversion rate decomposition, cohort-based funnel analysis • Outcome: Visibility into where prospects drop off, what converts, and which segments drive the highest-value revenue Product & Growth Analytics • Tools: Mixpanel, Amplitude, GA4, product event tracking, SQL, dbt, cloud warehouses, BI tools, Segment, RudderStack • Techniques: Activation metrics, retention and cohort analysis, feature usage tracking, lifecycle segmentation, product-to-revenue linkage • Outcome: Clear understanding of how product behavior impacts conversion, expansion, and long-term customer value RevOps & Go-To-Market Performance • Tools: HubSpot, Salesforce, Stripe, SQL, dbt, cloud warehouses, Excel • Techniques: Pipeline modeling, revenue timing logic, forecast vs actuals, customer segmentation by channel and product • Outcome: Unified views of pipeline health, bookings, revenue, churn, and growth efficiency across the go-to-market engine Data Modeling & Metric Layer • Tools: SQL, dbt, star schemas, semantic layers, Excel for validation • Techniques: Dimensional modeling, KPI definitions, metric governance, reconciliation across marketing, product, and revenue data • Outcome: Consistent metrics such as CAC, LTV, payback, activation, retention, and growth efficiency across all dashboards Dashboards & Automation • Tools: Power BI, Tableau, Looker, Python, Airflow, cloud warehouses (AWS, Azure, GCP) • Techniques: Automated pipelines, incremental models, QA checks, self-serve dashboard design for growth teams • Outcome: Decision-ready marketing, funnel, and executive dashboards that replace manual reporting Engagements range from ongoing growth analytics support to attribution builds, funnel and product analytics projects, and full reporting audits, all focused on giving teams a single, trusted view of how marketing and product actually drive revenue.

⭐ Expert-Vetted Top 1% AI Consultant on Upwork ⭐ Experienced AI Consultant with 10+ years working in top-tier research with MIT professors & founding 2 VC-backed startups (over $1M of entrepreneurial insights and lessons learned). I've helped 50+ businesses make efficiencies and scale through AI: sfailabs .com Recent business case studies: ⭐ AI transformation for a $2B private equity firm for their sales & marketing pipeline. ⭐ Helped a healthcare team cut admin processes by 40% through LLM-driven automation ⭐ Guided an enterprise finance department to build their proprietary AI copilot. ⭐ Streamlined project documentation with AI to save 20 hours per week for a construction firm. My services: 🎨 AI Architecture Design 🚀 AI Development (Agents, Platforms, Products) 🔍 AI Commercialization Advising 🤖 AI Strategy for Market Trends and Insights 🧠 CTO | Tech advisor | Consultant – I can join your team on a partial basis How I can help: 💼 Identify your best AI opportunities in your business or market 🧠 Design and build your custom AI (agent, platform, product) 💸 Launch your AI to maximize profit & impact First-author on AI conference papers (ICRA, AAAI, ICCM) and US Patent holder #405505-561P01US. I obtained a M.S. of Computer Science from Brown University, later awarded a Research Fellowship by the National University of Singapore. Founder of VC-backed AI companies with diverse industry applications. Sharing Knowledge in: ✅ AI Consulting Generative AI Consulting, AI Automation Consulting, AI Opportunity Assessment, Workflow Audit, Use-Case Prioritization, ROI Modeling, Build-vs-Buy Analysis, Vendor Selection, AI Governance, Production Readiness Assessment, and Fractional AI CTO Services. ✅ AI Workflow Automation AI Workflow Automation, Business Process Automation, n8n, Make, Zapier, CRM Automation, Email Automation, Approval Workflows, Document Routing, Data Synchronization, Event-Driven Workflows, and Human-in-the-Loop Automation. ✅ AI Agents & Copilots AI Agent Development, Agentic Workflows, AI Copilots, Internal AI Assistants, Multi-Agent Systems, Agent Memory, Agent Orchestration, Tool Calling, Function Calling, Structured Outputs, Model Context Protocol (MCP), LangGraph, CrewAI, and AutoGen. ✅ RAG & Enterprise Knowledge Systems Retrieval-Augmented Generation (RAG), Agentic RAG, Enterprise Knowledge Bases, Semantic Search, Hybrid Search, Vector Databases, Permission-Aware Retrieval, Source Attribution, Document Chunking, Embedding Pipelines, and Retrieval Evaluation. ✅ Document Intelligence Intelligent Document Processing, PDF Data Extraction, Contract Analysis, Invoice Processing, Form Processing, Document Classification, Table Extraction, Metadata Extraction, Document Summarization, Validation Workflows, and Exception Handling. ✅ LLM Application Development OpenAI API, Anthropic Claude, Google Gemini, Llama, Mistral, LangChain, LlamaIndex, Prompt Engineering, Structured Data Extraction, Multimodal AI, Fine-Tuning, LoRA, QLoRA, and Hugging Face. ✅ Enterprise Integrations Salesforce Automation, HubSpot Automation, Slack Integrations, Microsoft Teams Integrations, Google Workspace Automation, Notion Integrations, REST APIs, Webhooks, OAuth, SQL, NoSQL, ETL Pipelines, and Data Connectors. ✅ AI Evaluation & Guardrails LLM Evaluation, Prompt Testing, Hallucination Detection, Retrieval Testing, Output Validation, AI Guardrails, Model Monitoring, Human Review Workflows, Audit Logging, Access Controls, and Production Observability. ✅ Production AI Infrastructure AWS, Microsoft Azure, Google Cloud Platform, Docker, Terraform, CI/CD, GitHub Actions, FastAPI, Microservices, Model Serving, Scalable Inference, Secrets Management, and Cloud Deployment.

With over 20 years of extensive experience in software development, a strong foundation in a variety of programming languages, and a proven track record in delivering efficient and scalable software solutions, I am confident in my ability to contribute effectively to your team. I specialize in full stack development, data engineering, database design, cloud migration, API integrations, and enterprise application modernization. My main technical strengths include .NET, C#, React, Angular, SQL Server, PostgreSQL, AWS, Azure, ETL, SSIS, Power BI, Tableau, Docker, Kubernetes, and microservices. Throughout my career, I have worked with healthcare, fintech, government, aviation, and enterprise clients. I have built web applications from the ground up, optimized slow systems, designed data warehouses, created ETL pipelines, developed reporting dashboards, migrated legacy systems to modern cloud platforms, and led development teams through full project lifecycles. I can help with: • Full stack web application development • NET / C# backend development • React / Angular frontend development • SQL Server / PostgreSQL database design • ETL, SSIS, data warehouse, and reporting • AWS / Azure cloud deployment and migration • API integrations and microservices • Power BI, Tableau, and Grafana dashboards • Legacy system modernization and performance optimization I am comfortable working independently or as part of a team, and I can take a project from requirements gathering and architecture through development, testing, deployment, and ongoing support. My goal is always to build solutions that are secure, scalable, reliable, and easy to maintain.