Daniel Yinanc, Developer in Toronto, ON, Canada
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Daniel Yinanc

Verified Expert  in Engineering

DevOps Developer

Location
Toronto, ON, Canada
Toptal Member Since
February 6, 2019

Daniel is a product manager with about a decade of experience in the field, particularly specialized in data science and machine learning domains. Having worked as a data scientist and principal consultant specializing in data science and product management, he has the required experience, skill set and maturity to assist any client on designing and leading development of the most strategic AI, Analytical and Big Data products.

Portfolio

Apple
Machine Learning, Artificial Intelligence (AI), Data Management Platforms, ETL...
Automation Anywhere
Machine Learning, Data Science, Graphs, Optimization...
Rainmaker Technologies Inc.
Machine Learning, Artificial Intelligence (AI), Computer Vision, GPT...

Experience

Availability

Part-time

Preferred Environment

Cybersecurity

The most amazing...

...thing I have done was to invent a refining technology while bootstrapping the first and only lean agile startup in the oil and gas industry.

Work Experience

Data Platform Engineering | Product Manager

2020 - 2022
Apple
  • Led and launched Asgard, a machine learning data platform encompassing artificial intelligence, MLOps, data analysis, data visualization, and data custodianship capabilities.
  • Managed the product design and development of an anomaly detection system for detecting faulty requests, employing a KNN clustering algorithm, using Caret with high accuracy, and reducing operator waste time by over 80 percent.
  • Directed the product design and development of a Chatbot, utilizing NLP via Rasa for reducing human intervention by 50 percent on Slack support channels.
  • Oversaw the product design and development of FleetView, a star-schema data warehouse combining information from 40+ services in a single pane of glass that reduced server assignment SLAs from 3+ weeks to less than a day.
  • Built a fully remote pipeline, DataOps, MLOps, machine learning, and architecture practice from the ground up, growing it to 20+ engineers and architects. Devised a training and career development plan, mentoring them to become 10x remote engineers.
Technologies: Machine Learning, Artificial Intelligence (AI), Data Management Platforms, ETL, Data Governance, Dashboards, Big Data Architecture

Principal Data Scientist | Technical Product Manager

2019 - 2020
Automation Anywhere
  • Managed the product design and development of novel graph traversal-based algorithms for identifying paths in the process. This algorithm is the core enabler of the Discovery Bot product, allowing auto-development of bots from discovered paths.
  • Led the design and development efforts for a novel process fingerprinting algorithm utilizing the KNN cluster. This algorithm allowed us to understand process inter-relationships, leading to the use of graph algorithms in ms and with very high accuracy.
  • Oversaw design and development for data pipelines ingesting process discovery data from client devices to a central data warehouse supporting data visualizations at a 50 percent less cost than competing vendor platforms.
  • Directed the design and development of a data lakehouse to serve as a core analysis, training, and model deployment platform leading to an increase of 10x the speed in machine learning model development and deployments.
  • Led a machine learning practice for the Discovery Bot in charge of a team of machine learning engineers, solving process mining and process discovery challenges via developing novel graph analysis and ML models.
Technologies: Machine Learning, Data Science, Graphs, Optimization, Artificial Intelligence (AI)

Data Scientist | Management Consultant

2014 - 2019
Rainmaker Technologies Inc.
  • Brought in to jump-start external clients’ startup products and get them up and running in data science, machine learning, eCommerce, and enterprise products domains.
  • Led and launched Raincheck, a coupon sales platform competing with LivingSocial and Groupon, in less than six months, as an MVP recovered the product from a failed product launch by prior management.
  • Directed product design and development for ChatFish, an industry insider AI ChatBot platform designed to be white labeled and marketed to realtors and medical professionals leading to a successful product launch.
  • Managed strategic product marketing efforts for an oil and gas startup that created a novel refining technology, reducing the refining process's carbon footprint by over 50 percent.
  • Oversaw product design and development efforts for a recommendation engine targeting the telecommunications industry's online checkout process, which led to a 20 percent decrease in abandoned shopping carts.
  • Built and managed product, design, and data science teams, supporting all machine learning, data strategy, and product design with a culture focused on tight collaboration, transparency, and mentoring within the work hard/have fun framework.
Technologies: Machine Learning, Artificial Intelligence (AI), Computer Vision, GPT, Generative Pre-trained Transformers (GPT), Natural Language Processing (NLP), Recommendation Systems, Market Segmentation

Data Scientist

2011 - 2014
Mawer Investment Mgmt Ltd.
  • Built a customer attrition random forest model for wealth management clients and improved monthly retention by 50 basis points for clients likely to change houses by providing timely support calls.
  • Partnered with the portfolio support team to identify customer segments to target using a K nearest neighbors (KNN) clustering algorithm, improving the cold call conversion rate by over 30 percent.
  • Conceptualized and developed a business intelligence, portfolio return analysis intranet web application that linked the company with external databases and delivered analysis in table, graphical, and pivot formats.
  • Compiled and analyzed equity and fixed income security price data, seeking anomalies for potential mispricing opportunities leading to over $10 million in trades.
  • Implemented a time series analysis to develop equity benchmarks to compare with internal equity models used in asset management, leading to reduced benchmark deviations and greater fund performance.
  • Served as a data custodian in charge of corporate data integrity and access security for security pricing and fund performance data.
Technologies: MongoDB, Mercurial, SQL, Talend, Object-relational Mapping (ORM), Microsoft SQL Server, Natural Language Toolkit (NLTK), Scikit-learn, Pandas, NumPy, Python, JavaScript, Node.js, NoSQL, Jakarta EE, Java

DevOpsicon

http://github.com/devopsicon
Purpose of DevOpsIcon organization is to demonstrate for the benefit of open source community, best practices involved in DevOpsifying a realistic app with realistic components:

- Rest Microservices (Sales, Expenses, and Users)
- Customer Facing (Hybrid Mobile App)
- Message Bus Microservices (Files)
- Tool agnosticity (all build tools can do the job)
- Language agnosticity (all languages can do the job)

Paradigms

Unit Testing, Functional Testing, DevSecOps, DevOps, ETL, Functional Programming, Concurrent Programming, Test-driven Development (TDD), Behavior-driven Development (BDD), Object-relational Mapping (ORM), Microservices, Penetration Testing, Data Science

Industry Expertise

Cybersecurity

Other

AWS DevOps, Cloud, Pipelines, Performance Testing, APM, Application Security, Information Security, Security, IT Security, Cloud Services, Agile Software Testing, Static Application Security Testing (SAST), Dynamic Application Security Testing (DAST), Security Audits, Relational Database Services (RDS), API Gateways, Artificial Intelligence (AI), Machine Learning, Boot, Tornado, Computer Vision, Natural Language Processing (NLP), Recommendation Systems, Market Segmentation, Graphs, Optimization, Data Management Platforms, Data Governance, Dashboards, Big Data Architecture, GPT, Generative Pre-trained Transformers (GPT)

Languages

Java, JavaScript, Scala, Erlang, SQL, Python

Frameworks

Spring Boot, Express.js, React Native, Akka, AngularJS, Hadoop, Spark, Django, Angular, Koa

Libraries/APIs

React, TensorFlow, Keras, Scikit-learn, Node.js, NumPy, Pandas, Natural Language Toolkit (NLTK)

Tools

Jenkins, Travis CI, CircleCI, RabbitMQ, Gradle, Git, Apache Maven, GIS, Mercurial, Terraform

Platforms

Kubernetes, Docker, VMware Tanzu Application Service (TAS) (Pivotal Cloud Foundry (PCF)), OpenStack, Azure, Jakarta EE, Android, Talend, Amazon EC2, Amazon Web Services (AWS)

Storage

MySQL, MongoDB, Elasticsearch, Microsoft SQL Server, Redis, Google Cloud, NoSQL, Sybase, PostgreSQL, Neo4j

2008 - 2010

Master of Engineering Degree in Telecommunications Engineering

University of Alberta - Edmonton, AB

2005 - 2007

International Master of Business Administration Degree in Innovation and Business

Schulich School of Business - Toronto, ON

2001 - 2005

Bachelor of Science Degree in Mathematics and Physics

Rutgers University - New Brunswick, NJ

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