Data Science Engineer (GCP)

Stacktics Inc.•Toronto, ON

32d•Remote

About The Position

The Data Science Engineer (GCP) will play a key role at Stacktics Inc., where we design, create, deploy, maintain and grow industry-leading Cloud Infrastructure, Big Data Analytics and Cloud For Marketing products, solutions and services. The ideal candidate will have hands-on experience in the end-to-end lifecycle of a data science project, from data ingestion and model development to production deployment and monitoring, using native GCP services. This role is for a highly technical practitioner who can transform research and prototypes into robust, scalable production systems.

Requirements

Bachelor's degree in Computer Science, Statistics, Mathematics, or a related quantitative field. Master's or Ph.D. is a plus.
3+ years of professional experience in a data science or machine learning role and advanced analytical workflows built on the cloud, GCP preferred
Strong understanding of statistical analysis of data, including correlation analysis, outlier analysis and hypothesis testing
Strong understanding of data visualisation concepts, different types of visualisation charts and choosing the appropriate visualisations to convey insights effectively
4+ years of experience building interactive dashboards using at least 1 data visualization tool such as Looker Studio, Tableau, or Power BI.
Proven hands-on experience with the Google Cloud Platform ecosystem.
Strong proficiency in Python and SQL.
Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
Solid understanding of machine learning principles, algorithms, and best practices.
Familiarity with containerization technologies, particularly Docker.
Experience in hyperparameter tuning and evaluation of ML models
Strong understanding of Feature Selection and Feature Engineering concepts
Experience using ETL/orchestration/workflow management frameworks like Apache Airflow preferred, but not required
Strong understanding of and experience with large-scale OLAP databases and data warehouses. Strong understanding of Google Cloud BigQuery preferred
Understanding digital marketing ecosystems and tools, such as Google Marketing Platform, GA360, Google Ads, and Adobe Suite, is an essential strong asset
Technical understanding of a range of marketing concepts, such as cookie-based data collection, setting and leveraging audience segments, attribution modelling, A/B testing, knowledge of marketing KPIs and their calculation will be a strong asset.
Excellent written & verbal communication skills are essential; the candidate should be comfortable presenting and participating in group discussions of concepts with internal and external stakeholders.

Nice To Haves

GCP certification (e.g., Professional Data Engineer, Professional Machine Learning Engineer).
Experience with GCP.
Experience in an MLOps-centric environment with knowledge of CI/CD and automation.
Familiarity with real-time data streaming and processing.
Experience with business intelligence tools like Looker or Tableau.
Strong problem-solving skills and a proactive, results-oriented attitude.

Responsibilities

Work with business stakeholders and data engineers to understand requirements, identify data sources, and develop solutions to complex and open-ended business problems.
Perform exploratory data analysis to identify patterns from historical data, generate and test hypotheses, and provide product owners with actionable insights.
Design, develop, and deploy machine learning models and pipelines on GCP.
Utilize core GCP services such as BigQuery for data storage and analysis, Vertex AI for model training and deployment, and Dataflow or Cloud Composer for building ETL/ELT pipelines.
Implement and optimize Marketing Mix Modeling (MMM) solutions on Google Cloud Platform.
Participate in the creation of Statements of Work and other Prospecting activities that require technical expertise and inputs.
Monitor and troubleshoot model performance in production, ensuring system reliability and efficiency.
Apply advanced statistical and machine learning techniques to a wide range of business problems, including forecasting, classification, and clustering.
Communicate complex concepts and results to both technical and non-technical audiences.
Maintain and exceed client satisfaction with Stacktics Inc.’ deliverables, day-to-day work and overall value as a partner
Cultivate opportunities for company growth, always seek areas where Stacktics Inc.’ role could be expanded
Adapt to ever-changing client needs and expectations
Maintain dedication toward achieving excellence in Stacktics Inc.’ delivery against client needs, and overall success as an organization.
Be an enthusiastic, positive and generally awesome team mate, mentor & constantly curious learner.
Stay up-to-date on relevant technologies, plug into user groups, understand trends and opportunities to ensure we are using the best possible techniques and tools.