Hire the Best Data Scientists
in Armenia

With a background in Data Science and hands-on experience in content moderation, SEO keyword optimization, and market research, I bring both analytical precision and creative problem-solving to every project. I have the skills of turning raw information into clear, actionable insights. Whether it’s cleaning and structuring datasets, ensuring content meets compliance standards, or boosting discoverability through targeted SEO, I deliver work that’s accurate, timely, and aligned with your goals. Skilled in Python, R, SQL, and Power BI, I’m ready to take your project from concept to completion with professionalism and attention to detail.

7+ years as a Computer Vision Engineer and AI Product Engineer building production OCR, image analysis, segmentation, ONNX/FastAPI inference, VLM/RAG, and OpenAI/Claude/OpenClaw workflows. I help teams move from AI demos to reliable products: model pipelines, backend APIs, review dashboards, human approval gates, monitoring, cloud deployment, and clean handoff. My strongest projects combine: • Computer vision: segmentation, detection, landmarking, image analysis, visual inspection • OCR/document AI: extraction, validation, structured outputs, reviewer workflows • AI product systems: OpenAI/Claude, OpenClaw, VLMs, RAG, source traces, confidence checks • Production engineering: Python, FastAPI, ONNX, OpenCV, PyTorch/TensorFlow, PostgreSQL, Cloud Run/AWS I am a good fit when the output must be accurate, reviewable, logged, and safe enough for real business use.

I build credit scoring and loan default prediction models that help lenders approve more good borrowers, cut losses, and make underwriting decisions they can stand behind. I work in Python, and I focus on models that go into production not prototypes that get shelved. Before Upwork, I spent three years as an in-house Data Scientist at Ameriabank, one of Armenia's largest banks, building forecasting and risk models used in live operations. That experience shapes how I work: I care as much about how a model holds up over time and under review as I do about its accuracy on day one. I usually work with: — Fintech and alternative/SME lenders building or improving credit decisioning — Banks and credit unions that need scorecards built, rebuilt, or validated — Risk and analytics teams that need an extra pair of expert hands What I typically deliver: — Credit scoring and application/behavioral scorecards — Loan default prediction and PD models — PD / LGD / EAD modeling and IFRS 9 ECL work [ADD REAL PROJECT DETAIL] — Model validation, monitoring, and clear documentation — Risk segmentation and lending portfolio analytics — Fraud detection models for lending — Risk dashboards and SQL/Python pipelines that replace fragile Excel reporting Tools I rely on: Python (pandas, scikit-learn, statsmodels), XGBoost, LightGBM, logistic regression, and SQL, with FastAPI and Docker when something needs to be deployed. A few honest signals: Top Rated Plus, 100% Job Success, and $40K+ earned on Upwork. On a recent credit scoring project the client's feedback was simply "Highly recommended," and another noted my "amazing knowledge in ML and DS." [ADD REAL METRIC e.g. Gini/AUC, default-rate reduction, or approval-rate lift] How I work is straightforward: a short scoping call, then a clear plan with an honest estimate, then iterative delivery with documentation your team and any reviewer can actually follow. If something isn't the right fit for me, I'll tell you. Send a short message with your problem, your data, and your timeline. I usually reply within a few hours. The first 15-minute scoping call is free.

Most data and machine learning projects do not fail because the models are wrong. They fail because real decisions are built on systems that were never designed for production reality. Data distributions change. Assumptions stop holding. Feedback loops appear once decisions are automated. What looks correct during analysis can quietly become wrong when it starts affecting real users, money, or operations. My work focuses on that gap between analysis and real-world execution. I design and implement production decision systems, not demos, notebooks, or isolated models. These are systems where predictions directly drive actions such as approvals, rejections, prioritization, allocations, or automated workflows. In this context, correctness, transparency, and operational control matter more than theoretical performance. My background combines applied machine learning, data engineering, and direct ownership of real decision pipelines. I have worked on systems used in environments where mistakes are costly, including credit decisioning and automated trading. I approach every project assuming that data will be imperfect and conditions will change over time. Models are components of a system, not the system itself. I work system-first. That means clearly defining decision logic, data contracts, monitoring signals, and conditions for retraining or rollback. A system should surface degradation early, before it causes damage, not after. What I do not do is equally important. I do not sell AI magic, guaranteed outcomes, or opaque black-box solutions. I do not optimize offline metrics without considering how the system behaves once deployed. If a system cannot be monitored, understood, and controlled in production, I do not consider it complete. Clients usually reach out to me when decisions matter, scale is real, and failure is expensive. If you need a system that behaves predictably under pressure and you want to clearly understand both its capabilities and its limits, we are likely a good fit.

Top Rates Plus - awarded to the top 3% of Upwork freelancers! Experienced Senior Statistical Programmer with over 8 years of expertise in clinical trials and pharmaceutical research across therapeutic areas including oncology, cardiology, dermatology, gastroenterology, neurology, hematology, Real World Evidence (RWE), peptides and vaccines studies. Strong leadership capabilities in coordinating programming activities and timelines across multiple studies in phases I-IV. Dedicated to maintaining data integrity and supporting efficient clinical trial operations. Proficient in the development of statistical computing environments and serving as a clinical trials subject matter expert (SME) for software development companies supporting clinical research solutions. For a detailed overview of my hands-on responsibilities and real-world contributions, please refer to the Employment section, which outlines how this expertise has been applied across clinical trial development and pharmaceutical research projects. I hold Bachelor of Data Science degree from the American University of Armenia. My educational background, combined with hands-on experience, has equipped me with a robust skill set and a deep understanding of statistical methodologies and programming languages relevant to the clinical trials domain. My technical skills include proficiency in: SAS Programming (Advanced Level Certified, see in the 'Certifications' section): • Advanced SAS/BASE, SAS, SQL, SAS/MACRO, SAS/GRAPH, SAS/STAT, SAS/PROC, ODS output • SAS Viya (cloud version), Integration with R and Python, SAS Visual Analytics • Arrays, Hash Objects, Advanced Indexing, Memory Management • Handling large and complex datasets with efficient I/O and parallel processing techniques • Advanced macro writing, debugging and dynamic code generation, nested and recursive macros • Git/version control tools R Programming: • Clinical packages - pharmaverse, admiral, sdtmoak, tfrmt, gtsummary, PKNCA • Data manipulation and transformation - tidyverse, dplyr, tidyr, purrr, stringr, lubridate, tibble (implicit), readr (implicit) • Data visualization - ggplot2, plotly, gtsummary (dual-purpose), gt, flextable, patchwork, cowplot • High-quality analytical reports - rmarkdown, knitr, quarto • Interactive dashboards and applications using R Shiny Python Programming: • Python core (data types, control flow, functions, modules), NumPy, pandas, SciPy. • Clinical data processing with pandas (joins, reshaping, group summaries, derivations comparable to SDTM/ADaM workflows). • Integration with SAS and R (reading/writing SAS datasets via pyreadstat, interoperability for QC and validation). • Data visualization and reporting (matplotlib, seaborn, Excel/CSV outputs, automated report generation). • Advanced data handling (vectorization, memory optimization, chunked processing, handling large datasets). • Statistical analysis in Python (descriptive statistics, hypothesis testing, regression, survival analysis using lifelines). • Validation and quality control frameworks (independent QC of SAS outputs, data consistency checks, audit-friendly logs). • Unit testing and code quality (pytest, structured logging, reproducible environments). • Metadata and XML processing (Define-XML handling, CDISC metadata validation using xml/lxml). Power BI & Business Intelligence: • Design and development of interactive Power BI dashboards for exploratory and operational analytics • Data modeling using Power BI semantic models, relationships, and star-schema concepts • Data transformation and preparation using Power Query (M language) • KPI development, filters, drill-downs, and slicers for executive-ready reporting • Integration with multiple data sources (CSV, Excel, SQL databases, APIs) • Performance optimization for large datasets (model size, relationships, DAX efficiency) • Secure sharing and collaboration using Power BI Service Project Management: Working with Jira, Scrum, GitHub Microsoft Office tools: Microsoft Word, Excel, PowerPoint, Access, Outlook Driven by a passion for continuous learning and a collaborative spirit, I am known for my easy-going demeanor and my ability to thrive in team environments within the clinical trials field. I approach each project with dedication and attention to detail, consistently delivering results that exceed expectations and contribute to the advancement of clinical research.

✅ EXPERT-VETTED 🎖 TOP RATED PLUS (Top 1% 🥇 of GLOBAL talent on Upwork). I am a Data Scientist, AI, Machine Learning, and Software Engineer with over 9 years of professional experience building software at any scale. I used to work at large companies such as Yandex as well as in many successful startups. Now I am running Shapeion Technologies, providing software and ML consulting for companies around the globe, to accomplish their business goals. I have been managing startup projects with client teams and have helped draft product roadmaps, planning, and talent acquisition. I have a good network of engineer talent who can help build product MVPs effectively. Products made by me helped startups to raise millions of USD. I have a team of 15 professional Data Annotation specialists who have completed many projects in the Natural Language Processing and Computer Vision fields. They are fluent in the following data annotation platforms: CVAT, Doccano, and ProdiGy. Here is a brief summary of my expertise: ● 2000+ worked hours and 30+ projects completed PERSONALLY only at Upwork ● Created MVPs for various startups and companies that raised millions of USD ● Helped 30+ businesses to reach their goals in time I am proficient in: ✅ Data Science and Machine Learning: ● classification and regression tasks ● time-series prediction (ARIMA, ...) ✅ Natural Language Processing (NLP): ● Text classification (including Sentiment Analysis, Aspect-Based Sentiment Analysis) ● Named Entity Recognition (NER, automatic extraction of relevant entities, like names, locations, dates, etc) ● Chat-Bots (Deep Learning or Rule-Based chat-bots for various domains) Frameworks: SpaCy, HuggingFace, Transformers, NLTK, Langchain, Pinecone Annotation platforms: Doccano, ProdiGy, Clarifai Architectures: BERT, LongFormer, GPT-3, GPT-4 Domains: MedTech, E-Commerce, HRM, AD-tech ✅ Computer Vision (CV): ● Image Classification ● Object Detection (YoLo) ● Instance segmentation / Semantic Segmentation (Mask R-CNN) ● Optical Character Recognition (OCR) Frameworks: PyTorch, TensorFlow, Keras, DarkNet, Detectron, Detectron2, Fast.ai Annotation platforms: CVAT, Clarifai Domains: Medical Imaging, CCTV (surveillance), NFT, LegalTech (document analysis) ✅ Full-Stack Development: ● Backend (FastAPI, Flask, Django, django-rest-framework, Node.js, JavaScript, PHP, Yii Framework) ● Frontend (Vue.js, React.js) ● WordPress ● CI/CD (Docker, docker-compose, Kubernetes, k8s, Ansible, Terraform) ● Databases (PostgreSQL, MySql, MongoDB, OracleDB, ArangoDB, ClickHouse, GraphDB) ● AMQ (Celery, RabbitMQ) Technical skills: Python, Javascript, Go, Java, Spring Boot, Gradle, Node.js, Angular, Tensorflow, Keras, NumPy, Serverless Frameworks, Docker, Terraform, Ansible, Kubernetes, Jenkins, Spinnaker, GitOps, DataOps, AWS. GCP, Azure, JAMstack, GraphQL, MEAN Stack, React, Redux, ES6, Express, MongoDB, Redis, Linux, Etcd, Consul, Kinesis, Redshift, DynamoDB, Spark, Hadoop, Kafka, PostgreSQL, MySQL, ELK, Git, Flask, and Django. Thanks for your consideration! "Alexander was excellent. He managed expectations well and overperformed on the work. Communications were excellent. He saved us 100s of hours of work by automating our processes. He's more expensive than many people on Upwork, but appears to be exceptionally good an reliable." - Tom Mather