More then 10 years of academic and industry experience as research data scientist and data analyst with proven machine learning skills I can deliver high-quality work with precision and expertise. Experienced in following ✅ Data Analysis (process data, prepare data, analyse data , present insights ) Python | Excel | R | Tableau | Power Bi | Google sheets ✅ SQL Proficient in crafting complex queries for data extraction, transformation, and analysis. BigQuery ✅ Python & R programming Employing these languages for data cleansing, modeling, and machine learning. ✅ Data visualisation (Tableau, Python matplotlib, seaborn, plotly, Dash, R ggplot, Gephi, Cytoscape) ✅ Presentation and Reports (R and Python Notebooks, Report writing, slides presentations) ✅ Machine Learning (classification, clustering, regression analysis and reinforcement learning) ✅ Social Network Analysis (Node classifications, Community detections, Centrality Measures, Information diffusion ) With extensive experience in regression, classification, clustering, deep learning, and graph embedding techniques, I have the skills to turn your data into valuable insights. As a freelance data analyst, I have successfully completed various projects related to machine learning and social media analytics. As a highly motivated and results-driven individual, I thrive in fast-paced environments and can work independently or as part of a team. I am committed to delivering high-quality work on time and within budget. If you're looking for a skilled and experienced Machine Learning Engineer and Data Analyst, don't hesitate to contact me. I would be delighted to discuss your project and help you achieve your goals.

I am a skilled Data Scientist and Software Developer with expertise in Python, MATLAB, .NET (C#), and SQL. With a background in data science, machine learning, and software development, and formal methods. I specialize in creating efficient, scalable solutions for complex problems. What I Do Best: Data Science & Machine Learning – Data analysis, predictive modelling, AI-driven solutions. Python Development – Automation, data processing, API development, AI/ML algorithms. MATLAB Development – Numerical simulations, control systems, signal processing. .NET & C# Development – Desktop applications, backend services, enterprise software. SQL & Database Management – Query optimization, database design, data engineering.

I am having 4+ years of experience as a Data Professional specializing in Data Engineering, Data Analysis, Web Scrapping, ML, Data Warehousing and Big Data with a Bachelor's degree in Data Sciences. Proficient in Python, SQL, R, C/C++, C#, Java, and tools such as Hadoop, Power BI, Protege Owl, Kudo, Hive, Spark, Impala, ODI, and Oozie. Possesses a fair understanding of Cloud technologies like AWS and Cloudera. Passionate about leveraging data for informed decision-making. Open to exciting opportunities. Core Competencies: ★ Data Science ★ Web Scrapping ★ Machine Learning ★ ETL ★ Exploratory Data Analysis ★ Python ★ Data Engineering ★ Big Data ★ MLops ★ Business Intelligence ★ Data Analytics ★ Knowledge Graphs ★ Data Visualizations Tools: Hadoop / Apache Hive / Apache Spark / ODI / Oozie / Kudo / Impala / Jupiter Notebook / Git / Eclipse (IDE) / Power BI / R Studio / Graph DB / AWS Cloud / Cloudera / Protege Owl / Docker / Kubernetes / Jenkins / ML Flow / Air Flow / Google Colab Framework & Libraries: Pyspark / Pandas / Plotly / Seaborn / Matplotlib / Numpy / BeautifulSoup / Scrapy / Selenium / Keras / Pytorch / Tensorflow / Scikit-Learn / Programming Languages: Python / SQL / R / Java / Turtle / C, C++, C#

I build LLM data pipelines, forecasting models, and production APIs for founders and small teams. From one-time analysis to product-grade systems. I co-founded a market-data startup, where I built an NLP pipeline that labels 1.5M+ news articles and shipped a production API. My research on LLM rerankers was accepted at SIGIR 2026, a leading conference for search and ranking systems. I also maintain open-source LLM tools, including a LangGraph agent CLI on PyPI and a local RAG tool with page-cited answers. I have a strong track record in: • LLM data pipelines: classification, labeling, sentiment scoring, and extraction • Production ML systems and APIs (FastAPI, Docker, AWS, Google Cloud, BigQuery) • Forecasting models for sales optimization and budget planning • Dashboards and decision tools • CRM data analysis (HubSpot, Zoho) • RAG systems and LLM agents (LangGraph), with testing and evaluation Founders and team leads typically work with me to: • Replace manual labeling, tagging, or reporting work with automated LLM pipelines • Add an AI feature to an existing product and make it reliable enough to ship • Build forecasting models on transaction, sales, or CRM data • Extract insights from complex data such as transactions, call records, and multi-source attributions • Turn an LLM prototype into a tested, deployed system I have 3+ years of freelance experience and 5+ years of hands-on data science and analytics. I've worked directly with founders and small teams, and delivered 40+ projects with a 100% success rate. I hold a Master's in Computer Science and a bachelor's degree in business, and I conduct applied research in machine learning for finance and NLP. What previous clients say: "Baris will always be the #1 choice in his category. Great guy. 10/10." "One of the best freelancers I've worked with. He understood quickly what I was trying to build." For larger projects, my usual structure is a short paid discovery to map the problem and the data, then a fixed-price build with clear milestones, so the budget is known before the work starts. Ongoing support is optional after that. If you have an LLM or data problem that needs to work reliably in production, feel free to send a message. I'll be happy to take a look.

Senior AI/LLM engineer for enterprise teams. Built a system that saved 40 hrs/week of expert time by automating knowledge retrieval across 23 years of project data. I build for production, not demos. How I Can Help You Scale: ✅ AI Agent Development & Generative AI: I don't build toy demos. I ship production-grade multi-agent systems, RAG pipelines, and agentic workflows using LangGraph, LlamaIndex, Claude, and GPT-4. I design the full intelligence layer: memory architecture, retrieval logic, orchestration, and evaluation frameworks using RAGAS and Langfuse. ✅ Data Engineering & ETL/ELT: I architect clean, scalable data warehouses in Snowflake, Microsoft Fabric, and Redshift. My pipelines built with Apache Airflow, dbt, and Airbyte are designed to be reliable, well-documented, and maintenance-free. I have delivered full Microsoft Fabric medallion architectures from Bronze through to Gold and the Semantic Model layer for enterprise clients operating across multiple countries. ✅ Machine Learning & Predictive Analytics: From 15-year demand projections for industrial firms to stock return pipelines analysed over 23 years of market data, I turn raw numbers into high-conviction forecasts. My models combine econometric rigour with modern ML to handle real-world uncertainty, not just clean benchmark datasets. ✅ Business Intelligence & Dashboards: I create BI-ready semantic models and intuitive dashboards in Power BI, Looker Studio, and Apache Superset, connected to production-grade data models underneath, not spreadsheets dressed up as dashboards. Why Clients Work With Me: ✅ I have worked across carbon markets, fintech, non-profits, supply chain, SaaS, and logistics. I understand the domain before I touch the stack, not just the tools. ✅ I operate as an individual engineer, technical lead, or AI product manager depending on what the engagement needs. ✅ My work is clean and well-documented. I communicate in plain English, so I embed into teams without friction and hand over systems that do not fall apart after I leave. I am available for project-based builds or ongoing retainer engagements. Drop me a message with a rough description of the problem you're solving. That is always the best place to start.

💼 🇨🇦 Canadian CFA Charterholder | AI-Native Fractional CFO for Startups | Runway, Fundraising, FP&A & AI Business Models | $1B+ Supported Capital Raises | Top Rated Plus AI startups move faster than traditional finance teams can handle. Revenue models change. Token costs fluctuate. Gross margins compress. Usage scales unpredictably. Investors ask sharper questions. Founders need more than bookkeeping, historical reporting, or another spreadsheet. They need a CFO who understands both startup finance and the emerging economics of AI-native companies. I’m a Canadian CFA Charterholder, Top Rated Plus Upwork fractional CFO, with Masters in AI and ML training. I help founder-led startups build finance functions that are faster, more automated, more investor-ready, and more useful for strategic decision-making. Across my career, I’ve supported startups, growth companies, and investor-backed businesses through fundraising, liquidity pressure, board reporting, restructuring, financial modeling, and high-stakes strategic decisions. My models and finance systems have supported over $1B in capital raised across North America and Europe. What I Help Clients Do ✅ Extend runway and control burn 13-week cash models, runway analysis, burn multiple tracking, hiring plans, downside scenarios, and survival planning. ✅ Understand AI-native economics Token costs, compute expense, usage-based pricing, AI credits, gross margin pressure, customer profitability, cohort economics, and scalable monetization models. ✅ Build investor-grade financial models Three-statement models, SaaS models, marketplace models, usage-based revenue models, scenario cases, board models, and fundraising forecasts. ✅ Create an AI-powered finance function Automated reporting, KPI dashboards, variance analysis, forecasting workflows, anomaly detection, and AI-assisted CFO memos. ✅ Prepare for fundraising Seed through Series B models, bridge rounds, down-round planning, investor decks, data rooms, board materials, diligence support, and financial narratives that withstand scrutiny. ✅ Turn finance into a decision system Real-time dashboards, unit economics, pricing strategy, margin analysis, KPI discipline, and operating leverage planning. Core Services • AI-native Fractional CFO services • Startup FP&A, budgeting, forecasting, and scenario planning • Cash flow, liquidity, and runway management • 13-week cash flow models and crisis finance • SaaS, marketplace, subscription, and usage-based financial models • Token economics, compute cost, AI credit, and gross margin analysis • Fundraising support: Seed, Series A, Series B, bridge rounds, and investor defense • Board reporting, investor updates, and CFO memos • KPI dashboards in Power BI, Excel, and SQL • Finance automation using AI-assisted workflows • Pricing strategy, unit economics, LTV/CAC, cohort analysis, and profitability planning • Due diligence, data rooms, valuation, 409A, M&A, and special situations Why Founders Work With Me Most finance professionals understand accounting. Some understand startup fundraising. Very few understand how AI is changing the financial architecture of startups. I combine: • CFA-level financial rigor • 19+ years of financial modeling and strategic finance experience • Top Rated Plus Upwork execution across hundreds of client engagements • AI/ML graduate training • Hands-on CFO experience inside an AI startup • Practical operator judgment under pressure The result is a finance function that gives founders more clarity, more control, and better decisions — without slowing the company down. Let’s Talk In AI startups, finance cannot be slow, backward-looking, or disconnected from the product. Your finance function needs to understand cash, growth, pricing, compute costs, investor expectations, and strategic risk — all at the same time. Send me a brief, and I’ll help you build a finance function that is investor-ready, AI-aware, automated, and designed for the next stage of growth.

I build data systems that run in production ... LLM extraction pipelines, automated ETL, and scraping infrastructure that doesn't break when the source changes. $30K+ earned on Upwork. 100% Job Success. Top Rated. 1,400+ hours delivered. What I've actually shipped: — An AI document extraction system for a construction asset platform: Gemini-powered pipeline that reads unstructured operation manuals and drawings, extracts structured asset data, and loads it into the client's platform. Deployed on Google Cloud Run with event-driven triggers. — A cricket analytics platform (Decidr Sports): real-time data extraction from live sources, processing pipeline, and decision-intelligence dashboards. 400+ hours, client endorsed for being "solution oriented" and "accountable for outcomes." — LLM-based data normalization for a US insurance brokerage: messy carrier data in, clean standardized records out ... replacing hours of daily manual work. — Dozens of scraping and automation builds: Scrapy, Playwright, Selenium, anti-bot handling, deployed with Docker on AWS and GCP, scheduled and monitored so they keep running after I hand them off. How I work: I ask the right questions up front, propose the simplest architecture that solves the problem, and deliver something documented and maintainable ... not a script that dies in a month. Clients keep me on retainer because things I build stay running. Stack: Python, LLM APIs (Claude, Gemini, GPT), Scrapy, Playwright, PostgreSQL, MongoDB, AWS (Lambda, S3, ECS), Google Cloud Run, Docker, Make, n8n. If you have messy data, a manual process eating your team's time, or a source you need extracted reliably ... send me the details and I'll tell you exactly how I'd approach it.

AI Data Annotation & LLM Evaluation Specialist. Trusted by Upwork Enterprise clients for RLHF, DeepResearch response rating, chart analysis, and Q&A creation. Quantitative Economist — I catch what annotators miss. Top Rated. 100% Job Success. 5.0 ⭐ on every reviewed contract. Most annotators tick boxes. I apply statistical rigor — because I was trained as a Quantitative Economist before I was a labeler. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ WHAT I DO ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🔹 LLM & AI Response Evaluation RLHF, DeepResearch rating, response ranking, factuality checking, hallucination detection, SFT data review, preference labeling, red-teaming. 🔹 Data Annotation & Labeling Chart analysis, Q&A pair creation, image/text classification, NER, sentiment, taxonomy design, rubric writing, annotation guidelines. 🔹 Forecasting & Predictive Analytics ARIMA, SARIMA, Prophet, LSTM, XGBoost — sales, demand, inventory, financial forecasting. 🔹 Quantitative & Econometric Modeling Regression, classification, VAR, cointegration, causal inference, Blanchard-Perotti fiscal dynamics (yes, I actually built one). 🔹 EDA & Statistical Analysis Hypothesis testing, A/B testing, outlier detection, correlation, causality — in plain English. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ TOOLKIT ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Languages: Python, R, SQL, SAS ML/Stats: Scikit-Learn, Statsmodels, XGBoost, Prophet, TensorFlow Data: Pandas, NumPy, Excel, Tableau, Power BI, Streamlit, Plotly Annotation: LabelBox, Scale, custom rubrics ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ WHY CLIENTS REHIRE ME ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ✅ Economist brain — I think in causality, not correlation ✅ Accountable for Outcomes, Detail Oriented, Clear Communicator (real Upwork badges from real clients) ✅ No yes-man — I flag when data is lying ✅ Plain-English explanations of p-values and confidence intervals Hit "Invite to Job" — let's look at your data.

I take OpenClaw deployments from "stood up fast and left fragile" to production-grade infrastructure that survives real audits, real attack surface, and real business workflows. Recent engagements include a multi-agent OpenClaw commerce platform that lifted e-commerce revenue 34% in six months while serving 500K+ daily interactions at sub-200ms latency, and a self-hosted Mac Mini OpenClaw deployment for a regulated client that passed first-pass security review with zero rework. I work exclusively on self-hosted and VPS OpenClaw environments. No managed shortcuts, no vendor lock-in, no SaaS dependency. Every deployment I hand off is documented, audited, and fully owned by your team from day one. Most OpenClaw installs I inherit fail the same predictable way: API keys in plaintext, gateways exposed to the public internet, containers running as root, no skill auditing, no human-in-the-loop, and zero documentation when something breaks at 2 AM. I rebuild that foundation first, then layer integrations, automation, and compliance posture on top of infrastructure that actually holds up. If your OpenClaw is already running but feels held together with duct tape, I audit the existing config, reduce attack surface, fix drift, and document everything your team needs to own it. No rebuild required unless the foundation genuinely cannot be salvaged. Recent OpenClaw engagements include: • Architected a 12-agent OpenClaw commerce platform serving 500K+ daily interactions at sub-200ms latency, lifting revenue 34% and cutting cart abandonment 41% • Delivered OpenClaw on Mac Mini hardware for a regulated client with OS hardening, secrets rotation, and a full skill audit, passing first-pass security review with zero rework • Built repeatable OpenClaw deployment templates with documented upgrade paths, rollback procedures, and zero-downtime migrations across VPS, dedicated, and on-premise environments • Configured OpenClaw agent workspaces end-to-end: SOUL.md, job descriptions, skill assignments, approved-tools allowlists, and tightly scoped operating boundaries • Hardened OpenClaw infrastructure with non-root Docker containers, read-only workspaces, SSL, firewall rules, automated backups, and environment-specific tuning • Built OpenClaw secrets management for API keys, OAuth tokens, and environment variables with least-privilege access and documented rotation policies, never plaintext • Delivered OpenClaw security audits covering package-level risk review, permission lockdown, prompt injection and jailbreak testing, and gateway exposure analysis • Standardized OpenClaw production reliability with structured logging, health checks, lightweight alerting, and observability dashboards built for on-call engineers • Built an OpenClaw legal case management automation that cut manual workload 30% for a mid-sized law firm with every agent action audit-logged for compliance review • Deployed an OpenClaw customer support agent stack that resolved 78% of inquiries autonomously, reducing annual support costs by ~$180K • Implemented OpenClaw API integration layers connecting Claude, OpenAI, payment processors, shipping APIs, and CRM systems with OAuth and JWT authentication • Built OpenClaw skill auditing workflows with source-code review of every installed skill and human-in-the-loop confirmation on destructive actions I work best with teams running OpenClaw on their own infrastructure who want the foundation taken seriously, regulated-industry clients in legal, finance, and healthcare who need private AI agents with real data residency, and founders or IT leads who want OpenClaw automation that survives well past the demo. Typical engagements: OpenClaw production deployment (3 to 5 days standard), OpenClaw security audit and hardening, integration buildouts, and ongoing reliability retainers. My stack: OpenClaw, Anthropic Claude API, OpenAI API, Model Context Protocol (MCP), Python, Node.js, TypeScript, React, Next.js, Docker, Linux, PostgreSQL, MongoDB, AWS, Firebase, n8n, OAuth, JWT, REST APIs, and webhook orchestration. Native OpenClaw integrations across Gmail, Outlook, Office 365, Google Calendar, Slack, Microsoft Teams, Discord, Telegram, WhatsApp, Notion, HubSpot, Salesforce, Bitrix24, Google Drive, Dropbox, and any custom system reachable by API. Send a short note describing your current OpenClaw setup (or what you want to build), your hosting preference (VPS, dedicated, on-prem, or Mac Mini), any compliance constraints, and your deadline. I reply within the day with a concrete scope, timeline, and a short list of risks I see before we start. I work as a strategic OpenClaw partner on production AI infrastructure, not a ticket-taker.

⭐ "Trayambak has demonstrated absolute mastery of the subject matter. Even though the automation was in Spanish software, he adapted and understood it in record time. Highly, highly recommended." — Recent Client I build intelligent Python automations, reverse-engineer complex systems, and create secure data workflows that save businesses hundreds of manual hours. As a Certified Ethical Hacker (CEH) and ML Specialist, I specialize in building scalable solutions using Python, Machine Learning, cybersecurity practices, and advanced automation technologies. My focus is on creating practical systems that improve efficiency, security, and data-driven decision making. What I can help you with: • Complex Web Automation & API Reverse Engineering • Machine Learning model development and integration • Python backend development and API creation • Data analysis, processing, and visualization • Workflow and business process automation • Cybersecurity analysis and secure system design • AI chatbot development and automation tools • Technical project management for complex software systems I focus on writing clean, scalable, and secure code while delivering reliable solutions that create real business value for clients. If you are looking for someone who can transform technical ideas into working intelligent systems, I would be happy to collaborate with you. Let's talk!