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Tety Loscutoff
Verified Expert in Engineering
Data Scientist and Developer
Grimsby, ON, Canada
Toptal member since June 17, 2022
Bio
Tety is a technology entrepreneur who strives to provide clients with end-to-end service when creating new software solutions or revamping old ones. Some of the projects she has completed include financial and accounting systems, AI-powered document processing, forecasting, and anomaly detection. Tety has worked for clients across various countries and industries, including energy, government, education, and biotechnology.
Portfolio
MBA Assist
Python 3, Deep Learning, Django, JavaScript, Scikit-learn, Databases, R...
Adkins and Reid Holdings LLC
Python, SQL, Data Pipelines, Data Transformation, Data Cleaning, Data Modeling...
Waterside Commercial Finance
Artificial Intelligence (AI), Scraping, Open-source LLMs...
Experience
- SQL - 20 years
- Databases - 20 years
- Python 3 - 9 years
- Natural Language Processing (NLP) - 6 years
- Scikit-learn - 6 years
- Generative Pre-trained Transformers (GPT) - 6 years
- Django - 5 years
- Google Cloud Platform (GCP) - 4 years
Preferred Environment
Amazon Web Services (AWS), Google Cloud Platform (GCP), Machine Learning, Python, Financial Modeling, Language Models, Document Parsing, Agentic RAG Systems, Agentic AI, Selenium
The most amazing...
...project I've developed is an NLP system for extracting key information from regulatory reports of listed companies.
Work Experience
Director
2020 - PRESENT
MBA Assist
- Developed a system for short-term market forecasting. The system tracks performance over time using the online dashboard on the company's website. The market forecasting system is also available through an API with free and paid options.
- Became a top ML tutor in the Greater Toronto area.
- Helped over 50 clients with small and medium projects for over a year.
- Developed a system for the extraction of financial information and NER from annual reports of mining companies into a structured table format. The system leveraged several ML and NLP models, used in an ensemble to find the best results.
- Deployed the ensemble of ML/NLP models on ECS, using microservices and SQS/SES triggers. Integrated the pipeline with Snowflake and MySQL to deposit raw/processed data. Integrated with Sagemaker to track the performance of the models.
Technologies: Python 3, Deep Learning, Django, JavaScript, Scikit-learn, Databases, R, TensorFlow, Reinforcement Learning, Natural Language Processing (NLP), Generative Pre-trained Transformers (GPT), AWS Fargate, MongoDB, Linux, Data Science, Statistical Analysis, Decision Modeling, eCommerce, PyTorch, Machine Learning, NoSQL, Docker, Python, Amazon SageMaker, Non-fungible Tokens (NFT), Financial Data, Financial Modeling, Artificial Intelligence (AI), Text Analytics, Amazon Web Services (AWS), Jupyter, Amazon DynamoDB, Lambda Functions, Convolutional Neural Networks (CNNs), Object Detection, Keras, Cloud Infrastructure, Large Language Models (LLMs), Business to Business (B2B), B2B, Marketing Mix Modeling, Marketing Attribution, BigQuery, Google Analytics, Full-stack, Software Architecture, Technical Leadership, Computer Vision, Social Media, Social Media APIs, Architecture, Language Models, PDF, BERT, Document Parsing, Deep Neural Networks (DNNs), NLU, Test-driven Development (TDD), Market Research, Data Analytics, Data Analysis, Market Research & Analysis, REST APIs, Leadership, CTO, Google Cloud Datastore, Google Cloud, Optical Character Recognition (OCR), AWS Lambda, Generative Artificial Intelligence (GenAI), Dashboards, Large Language Model Operations (LLMOps), Hugging Face, LangChain, Meta Llama, OpenAI, Full-stack Development, Retrieval-augmented Generation (RAG), Open-source LLMs, Text Chunking Strategies, Scraping, Data Reconciliation, Data Engineering, Data Cleaning, Snowflake, FastAPI, PostgreSQL 9, Node.js, Data Pipelines, Dynamic Pricing, Pricing Models, Pricing Strategy, Competitive Strategy, Competitor Analysis & Profiling, Marketing Analytics, Customer Journey, Statistical Modeling, ML Pipelines, CI/CD Pipelines, Agentic AI, Agentic Workflow Design, Agentic Frameworks, RAG Systems, RAG Pipelines, Agentic RAG Systems, Machine Learning Operations (MLOps), AI Agents, Agentic Deployment, Terraform
Senior Data Engineer
2026 - 2026
Adkins and Reid Holdings LLC
- Developed an AI-powered state machine to automate scraping, parsing unstructured web results, and populating verified Salesforce records.
- Implemented AWS CloudWatch monitoring to track pipeline health and deliver automated daily success reports.
- Used AI agents to automate code generation and testing.
Technologies: Python, SQL, Data Pipelines, Data Transformation, Data Cleaning, Data Modeling, OpenAI, Claude, AI Data Classification, Document Parsing, CRM APIs, Skip Tracing, Web Scraping, Salesforce API, Machine Learning Operations (MLOps), AI Agents, Terraform
LLM Engineer and AI Developer
2025 - 2025
Waterside Commercial Finance
- Developed a batch scraper project with monitoring, error logging, and restart from the point of failure. I deployed the project as a GCP job, triggered on schedule.
- Built a model for classifying scraped company data into industries. I have used a combination of vector similarity search and OpenAI API batch scoring to achieve the best cost/performance ratio.
- Created a model to identify companies' locations based on incomplete data and find their population based on USDA and US Census data.
Technologies: Artificial Intelligence (AI), Scraping, Open-source LLMs, Large Language Models (LLMs), Python, Google Cloud Platform (GCP), Data Reconciliation, Data Cleaning, Data Analysis, Data Engineering, HubSpot CRM, ML Pipelines, CI/CD Pipelines, Agentic AI, Agentic Frameworks, Machine Learning Operations (MLOps)
SME Data Scientist
2024 - 2025
Minoro LTD
- Created multi-touch attribution models for several client datasets. Utilized advertising data from Meta, Google, TV ads, and catalog mailings to create a consolidated view of marketing effectiveness.
- Developed and implemented an algorithm to clean and reconcile data from different advertising reports to connect the journey of individual users through different websites, social media, and coupon touchpoints to their purchase activity.
- Deployed the solutions on Amazon ECS to ensure good performance on big data. Optimized existing algorithms to improve the processing performance.
Technologies: Machine Learning, Marketing Mix Modeling, Data Science, Marketing Attribution, Machine Learning Operations (MLOps), Full-stack Development, Data Reconciliation, Data Engineering, Data Cleaning, Snowflake, Data Pipelines, Dynamic Pricing, Pricing Models, Attribution Modeling, Google Ads, Marketing Analytics, Funnel Analysis, Statistical Modeling, ML Pipelines, CI/CD Pipelines, Terraform
Data Scientist
2024 - 2024
Bonify, LLC
- Built a topic labeling and classification tool for customer support tickets. Used a combination of classification, large-language, and statistical models to achieve the best cost-benefit ratio.
- Developed a web app to review and analyze topics and subtopics found in the user data. Deployed the app as a service on AWS.
- Built a tool to collect the data from an API and clean and organize the data according to dates, data attributes, and NLP-derived topics.
Technologies: Data Science, APIs, Unstructured Data Analysis, Big Data, Amazon Web Services (AWS), MySQL, User Journeys, Customer Journey, Amazon API Gateway, Mistral AI, Gemini API, Natural Language Processing (NLP), Topic Modeling, Semantic similarity, Streamlit, Visualization, Hugging Face, Generative Artificial Intelligence (GenAI), Large Language Model Operations (LLMOps), Meta Llama, OpenAI, Full-stack Development, Text Chunking Strategies, Data Reconciliation, Data Engineering, Data Cleaning, PostgreSQL 9, Data Pipelines, HubSpot CRM
Data Scientist
2023 - 2023
Pivotal Consulting Group, LLC
- Developed several multichannel attribution models for marketing activities of PCG clients. The models were based on the Markov-Chain process, first and last touch attribution, and linear attribution modeling.
- Developed an API application for managing PCG clients, auto-generating pixels, enabling and disabling client websites, and channel tracking. My role included the design, architecture, and full implementation of a Django app on Cloud Run.
- Managed a Google Cloud platform and the database collecting data for client modeling.
- Assisted the front-end developer with understanding the requirements and front-end implementation.
- Automated the model calculation on a daily basis to improve the API's responsiveness.
- Implemented queues and schedules to manage customer click data asynchronously.
Technologies: Python, Machine Learning, Marketing Attribution, Business to Business (B2B), B2B, Data Science, Marketing Mix Modeling, Attribution Modeling, JavaScript, Google Analytics, Salesforce API, BigQuery, Full-stack Development, Data Reconciliation, Data Engineering, Data Cleaning, PostgreSQL 9, Data Pipelines, Google Ads, Marketing Analytics, Funnel Analysis, ML Pipelines
Machine Learning Manager
2019 - 2020
MultiChoice
- Recruited and coached a team of ML engineers. I have built a team from scratch and completed a forecasting project, content recommendation system, and fraud detection system.
- Implemented an agile development process within my team, which served as an example for other teams in our department.
- Established stakeholder cooperation across the company. I have led data science and ML programs across departments.
Technologies: Python 3, Scikit-learn, Django, GraphQL, Azure ML Studio, Databricks, Spark, Databases, Reinforcement Learning, Linux, Data Science, Statistical Analysis, Decision Modeling, Machine Learning, Docker, Python, Amazon SageMaker, Financial Data, Financial Modeling, Artificial Intelligence (AI), Text Analytics, Amazon Web Services (AWS), Jupyter, Convolutional Neural Networks (CNNs), Keras, Cloud Infrastructure, Azure, Marketing Mix Modeling, Marketing Attribution, Full-stack, Software Architecture, Technical Leadership, Social Media, Social Media APIs, Architecture, Language Models, PDF, Document Parsing, Deep Neural Networks (DNNs), NLU, Test-driven Development (TDD), Data Analytics, Data Analysis, Kubernetes, REST APIs, Leadership, Chatbots, AWS Lambda, Dashboards, Full-stack Development, Vector Databases, Scraping, Data Reconciliation, Data Engineering, Data Cleaning, PostgreSQL 9, Data Pipelines, Competitive Strategy, Attribution Modeling, Google Ads, Marketing Analytics, Customer Journey, Funnel Analysis, Statistical Modeling, ML Pipelines
Chief Data Scientist | Founder
2018 - 2019
Futuresgroup NL
- Designed and implemented a system for tracking international trade. The system processed and reconciled a large volume of data to analyze and forecast international trade and changes in political situations.
- Researched, designed, and developed an international investment risk and opportunity analysis dashboard. The system was based on structured and unstructured data, including news, collected from various sources.
- Implemented an agile development process in my team.
Technologies: Python 3, SpaCy, Dash, Tableau, MongoDB, Linux, Databases, Generative Pre-trained Transformers (GPT), Natural Language Processing (NLP), Django, Scikit-learn, Data Science, Statistical Analysis, Decision Modeling, Machine Learning, NoSQL, Docker, Python, Modeling, Financial Data, Financial Modeling, Artificial Intelligence (AI), Text Analytics, Amazon Web Services (AWS), Jupyter, Cloud Infrastructure, Business to Business (B2B), B2B, Full-stack, Software Architecture, Technical Leadership, Social Media, Social Media APIs, Architecture, Language Models, PDF, Computer Vision, Document Parsing, NLU, Test-driven Development (TDD), Data Analytics, Data Analysis, REST APIs, Leadership, CTO, Dashboards, Full-stack Development, Text Chunking Strategies, Vector Databases, Scraping, Data Reconciliation, Data Engineering, Data Cleaning, PostgreSQL 9, Data Pipelines, Pricing Models, Pricing Strategy, Competitive Strategy, Google Ads, Funnel Analysis, Statistical Modeling, ML Pipelines
Consultant
2017 - 2018
Control Risks
- Used anomaly detection algorithms to detect transactional data. These data helped the conviction of members of a credit fraud syndicate in a bank.
- Detected insurance fraud syndicates using machine learning algorithms.
- Worked on fraud detection projects with teams in the Middle East, South Africa, and the USA, preprocessing large volumes of data for analysis.
- Developed sales lead tracking and management web system.
Technologies: Python 3, SAP, Tableau, QlikView, Databases, Natural Language Processing (NLP), Generative Pre-trained Transformers (GPT), Django, Scikit-learn, Data Science, Statistical Analysis, Decision Modeling, Machine Learning, Python, Modeling, Financial Data, Financial Modeling, Artificial Intelligence (AI), Text Analytics, Amazon Web Services (AWS), Lambda Functions, Keras, Cloud Infrastructure, Business to Business (B2B), B2B, Full-stack, Software Architecture, Technical Leadership, Social Media, Social Media APIs, Architecture, Language Models, PDF, Document Parsing, NLU, Test-driven Development (TDD), Data Analytics, Data Analysis, REST APIs, Leadership, Dashboards, Full-stack Development, Text Chunking Strategies, Vector Databases, Scraping, Data Reconciliation, Data Engineering, Data Cleaning, PostgreSQL 9, Statistical Modeling
IT Consultant
2007 - 2017
EOH Holdings
- Built several ML models for energy demand forecasting.
- Developed an SMS-based scheduler and notification system for power station maintenance.
- Used data science tools to develop a municipality revenue improvement system.
- Created the design and architecture of web-based climate change monitoring and evaluation system.
Technologies: Python 3, .NET, Java, Oracle, R, SQL, Databases, Linux, Data Science, Statistical Analysis, Decision Modeling, NoSQL, Python, Financial Data, Financial Modeling, Business to Business (B2B), B2B, Full-stack, Software Architecture, Technical Leadership, Architecture, Document Parsing, Test-driven Development (TDD), Data Analytics, Data Analysis, REST APIs, Leadership, Apache Kafka, Dashboards, Full-stack Development, Data Reconciliation, Data Engineering, Data Cleaning, Dynamic Pricing, Pricing Models, Pricing Strategy, Statistical Modeling
Experience
Detection of Brain Tumors on MRI
https://drive.google.com/file/d/1u6tE74yz2sFzVKVc1EOvbek6aicasWGH/view?usp=sharingI worked with a researcher to create a deep learning model that detected the shape of a brain tumor, if present, on MRI scans.
The input was taken from T1 and T2 scans saved in *.dcm files, and the output was presented in 3D Slicer software.
The input was taken from T1 and T2 scans saved in *.dcm files, and the output was presented in 3D Slicer software.
VoiceAPI
https://github.com/tetyanaloskutova/VoiceAPIAn API to generate voice recordings from a voice sample and text.
The API is deployable on AWS Fargate and uses the Tacotron PyTorch model for training and inference. Apart from voice generation, the API provides an option to fine-tune the model on new samples.
The API is deployable on AWS Fargate and uses the Tacotron PyTorch model for training and inference. Apart from voice generation, the API provides an option to fine-tune the model on new samples.
Day-Ahead Market Price Forecast Based on Media Trends
https://rapidapi.com/remote-works-default/api/media-obsessed-market/This project uses historical price moves and sentiment changes in the media to predict price moves for a range of stocks for the following day. The predictions are based on a number of ML models (linear models, ensemble models, and LSTM). The models are evaluated for the previous day, and the best-performing model is chosen for the next day. The project's historical performance is tracked and is available as an API endpoint and an online dashboard:
https://mbaassiste.herokuapp.com/
https://mbaassiste.herokuapp.com/
Education
2020 - 2021
Master's Degree in Physics
McMaster University - Hamilton, ON, Canada
2014 - 2017
Ph.D. in Business
University of the Witwatersrand - Johannesburg, South Africa
Certifications
NOVEMBER 2020 - PRESENT
Les Fondamentaux de la Négociation
ESSEC Business SchoOl Through Coursera.
MARCH 2015 - PRESENT
Economics of Competing Energy Sources
Stanford University
APRIL 2013 - PRESENT
Certified Wireless Engineer
Duxbury
DECEMBER 2012 - PRESENT
Certified Energy Manager
Association of Energy Engineers
MAY 2011 - PRESENT
Oracle SQL
Oracle
Skills
Libraries/APIs
TensorFlow, Scikit-learn, Social Media APIs, REST APIs, PyTorch, Keras, SpaCy, Salesforce API, Node.js
Tools
Amazon SageMaker, Jupyter, BigQuery, Terraform, Google Analytics, AWS Fargate, Azure ML Studio, Tableau, Claude
Languages
SQL, Python 3, Python, Snowflake, R, JavaScript, GraphQL, Java
Frameworks
Django, Agentic Frameworks, Spark, .NET, Streamlit, Selenium
Paradigms
B2B, Test-driven Development (TDD)
Platforms
Oracle, Google Cloud Platform (GCP), Amazon Web Services (AWS), Azure, AWS Lambda, Docker, Kubernetes, Google Ads, Databricks, Linux, QlikView, Heroku, Apache Kafka
Storage
Databases, NoSQL, Data Pipelines, MongoDB, Amazon DynamoDB, Google Cloud Datastore, Google Cloud, Amazon S3 (AWS S3), BigQ, MySQL
Industry Expertise
Social Media
Other
Natural Language Processing (NLP), Deep Learning, Data Science, Statistical Analysis, Decision Modeling, Machine Learning, Financial Data, Financial Modeling, APIs, Artificial Intelligence (AI), Text Analytics, Lambda Functions, Cloud Infrastructure, Large Language Models (LLMs), Business to Business (B2B), Full-stack, Software Architecture, Technical Leadership, Computer Vision, Architecture, Language Models, PDF, BERT, Document Parsing, Deep Neural Networks (DNNs), NLU, Data Analytics, Data Analysis, Leadership, Generative Pre-trained Transformers (GPT), Attribution Modeling, Dashboards, Machine Learning Operations (MLOps), Full-stack Development, Retrieval-augmented Generation (RAG), Data Reconciliation, Data Engineering, Data Cleaning, PostgreSQL 9, Pricing Models, Marketing Analytics, HubSpot CRM, Funnel Analysis, Statistical Modeling, ML Pipelines, Agentic AI, Agentic Workflow Design, RAG Pipelines, Agentic RAG Systems, AI Agents, Agentic Deployment, eCommerce, Modeling, Convolutional Neural Networks (CNNs), Object Detection, Marketing Mix Modeling, Marketing Attribution, Market Research, Market Research & Analysis, CTO, Chatbots, Optical Character Recognition (OCR), Marketing Research & Analysis, Customer Journey, Hugging Face, Large Language Model Operations (LLMOps), LangChain, OpenAI, Open-source LLMs, Text Chunking Strategies, Vector Databases, Scraping, Dynamic Pricing, Pricing Strategy, Competitive Strategy, CI/CD Pipelines, RAG Systems, Reinforcement Learning, Biostatistics, Numerical Methods, Statistics, Tax Accounting, Applied Physics, Negotiation, Wireless, Dash, SAP, Non-fungible Tokens (NFT), Regression, Generative Artificial Intelligence (GenAI), Unstructured Data Analysis, Big Data, User Journeys, Amazon API Gateway, Mistral AI, Gemini API, Topic Modeling, Semantic similarity, Visualization, Meta Llama, FastAPI, Competitor Analysis & Profiling, Data Transformation, Data Modeling, AI Data Classification, CRM APIs, Skip Tracing, Web Scraping
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