Int Data Science Engineer with strong Python, data modelling, GCP, and Apache Airflow to build an AI analytics product.
Job Type: Permanent
Positions to fill: 1
Start Date: Jun 27, 2022
Job End Date: Jun 27, 2022
Pay Rate: Salary: Negotiable
Job ID: 120309
Location: Toronto
Our client is a leader in the Venture Capital Space specifically focused on investing in FinTech Startup’s. They are looking for a Int Data Science Engineer with strong Python, data modelling, GCP, and Apache Airflow to build an AI analytics product.
Location: Remote
Project: Build an AI Product used to determine viable start up portfolio additions to our clients growing list of start up investments.
Must Haves:
Responsibilities:
Location: Remote
Project: Build an AI Product used to determine viable start up portfolio additions to our clients growing list of start up investments.
Must Haves:
- GCP technologies
- Build and maintain existing Apache Airflow DAGs
- Expert Python development skills – GCP big Query skills, grab data and store it. Used Tensor flow
- Building and maintain data APIs that power web applications and data dashboards
Responsibilities:
- Prototype new technology that supports our vision of making our consumer’s experiences better with our data
- Design, implement and maintain data pipelines for extraction, transformation, and loading of data from a wide variety of data sources using
- Provide support and insights to the business analytics and data science teams
- Work with stakeholders to assist with data-related technical issues and support their data infrastructure needs
- Work with Data Scientists and Machine Learning Engineers to build out robust and scalable pipelines and APIs
- Work on a data product that informs the investment teams of new start-up companies to invest in
- Gather overall market intelligence, including on: startups, funding, other venture funds, exits, trends by verticals (fintech, logistics, etc.), trends by countries, macro trends, etc.
- Design and implement work flows, procedures, and software to automate and improve data collection
- Streamline Human-CRM interactions via processes and automation
- Uses research, intuition, and experience to complement data