Data Scientist in North Vancouver, British Columbia at DarkVision Technologies

DarkVision is a Vancouver-based tech company that has been disrupting the industrial imaging market since 2013. We have created the world’s most advanced acoustic-based imaging platform, revolutionizing how our clients quantify and visualize the integrity of their critical assets.

Backed by Blackstone, one of the world’s largest private equity firms, DarkVision’s team of Software, Mechanical, and Machine Learning Engineers and Data Analysts is rapidly expanding to meet the demand for the company’s current and upcoming products.

Our employees work on cutting-edge technologies that blend science with real-world applications. We invite you to join our team for the exciting journey ahead as we become the global leader in industrial imaging.

DarkVision is seeking a Data Scientist to join our Imaging & AI team. You will ensure the statistical validity and business impact of our models by owning experimental design, causal analysis, and data integrity audits. You will be the bridge between our expert data analysis, machine learning models, and the actionable insights delivered to our clients.

DarkVision’s ultrasound imaging system collects huge datasets on the order of terabytes, involving sub-millimetric defects across assets that span hundreds of kilometers. Interpreting this data requires more than just black-box models; it requires rigorous statistical verification. You will focus on the development of analysis pipelines that validate our model performance and the creation of advanced visualizations that communicate complex results to stakeholders.

Working under the Imaging & AI team, you will join a multidisciplinary group of scientists and engineers. This team is responsible for early-stage ideation, research, experimentation, and development. You will collaborate closely with Machine Learning Scientists and Engineers to design experiments that prove the reliability of our technology.

• Experimental Design & Validation: Design and execute rigorous experiments to validate the performance of deep learning models. You will apply statistical methods to ensure our results are significant, reliable, and reproducible.
• Data Integrity & Analysis: Conduct deep-dive analyses and causal audits on our datasets. You will identify biases, anomalies, or quality issues in the data that could impact model training or production inference.
• Information Visualization: Create compelling 3D visualizations and automated reports that translate complex acoustic data into clear, client-facing insights for VPs and C-suite executives.
• Analysis Pipelines: Develop production-grade Python code to automate data processing and analysis workflows. You will ensure that statistical checks are integrated directly into our pipelines.

• Bachelor’s or Master’s degree in Statistics, Physics, Mathematics, or a related quantitative field, with substantial training in applied statistics.
• 3+ years of industry experience as a Data Scientist or in a related role.
• Strong proficiency in Python for data processing, statistical analysis, and visualization.
• Strong foundation in statistics and probability, including statistical modeling and hypothesis testing, with hands-on experience designing, running, and interpreting statistical studies.
• Ability to present statistical results clearly and rigorously using appropriate plots and visualization methods.
• Familiarity with AWS or similar cloud platforms for data storage and compute.
• Experience working with large, hierarchical datasets, including data held in non-relational storage.
• Strong communication skills to present complex statistical findings to senior non-technical audiences.

• Knowledge of Bayesian inference, time-series analysis, causal inference, and multivariate statistics.
• Experience designing A/B tests or clinical-trial-style validation studies for algorithmic products.
• Applied statistics experience in industrial or scientific settings, such as statistical process control, yield engineering, defect metrology, or experimental physics.
• Experience with GIS or geospatial data analysis.
• Experience visualizing and interpreting large 3D datasets, such as volumetric imaging or point cloud data.
• Experience analyzing high-dimensional, unstructured data (images, signals, or acoustic waveforms) rather than just tabular data.
• Advanced academic research experience (MSc, PhD) in Statistics, Physics, Mathematics, or other related fields.
• Track record of peer-reviewed publications in applied statistics, physics, or related fields.

For this role, we anticipate paying $100,000 to $150,000 per year. This role is eligible for variable pay, issued as a monetary bonus or in another form.

Keywords: Data Scientist, Applied Statistics, Probability, Experimental Design, Bayesian Inference, Causal Analysis, Python, AWS, Cloud Computing, Signal Processing, 3D Visualization, GIS.