Senior Data Analyst

Canopy•Detroit, MI

18h•Hybrid

About The Position

Join Canopy, a Ford-backed company, at the forefront of engineering advanced threat detection and deterrence products specifically designed for vehicles. Our mission is to eliminate vehicle crime and enhance mobility through cutting-edge consumer hardware, aftermarket connectivity, and AI-driven security solutions. As part of our team, you'll be at the forefront of innovation, helping to solve one of today’s most pressing challenges with cutting-edge solutions. As a Senior Data Analyst reporting to the Team Manager of Core AI and Data, you will spearhead the design, development, and implementation of cutting-edge machine learning models and algorithms to address intricate business challenges. Your role will involve analyzing large datasets to identify meaningful patterns, trends, and relationships, using a combination of statistical methods, machine learning techniques, and data visualization tools. Additionally, you will be responsible for developing and validating approaches that ensure accuracy, robustness, and scalability for production deployment.

Requirements

Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.
5+ years of experience in data science, with a strong background in statistical analysis, machine learning, and predictive modeling.
Proficiency in programming languages such as Python.
Strong expertise in SQL and experience working with large-scale databases and data processing frameworks.
Demonstrated ability to work with complex data sets, including data cleaning, transformation, and feature engineering.
Experience with data visualization tools such as Tableau, Grafana, or Matplotlib to present insights and results effectively.
Strong problem-solving skills, with the ability to work independently and manage multiple projects simultaneously.
Excellent communication skills, both written and verbal, with the ability to convey complex technical concepts to non-technical stakeholders.

Nice To Haves

Master’s or Ph.D. in Data Science, Computer Science, Statistics, or a related field.
Experience with deep learning techniques and frameworks such as TensorFlow, or PyTorch.
Familiarity with cloud computing platforms like AWS, Azure, or Google Cloud.
Experience where data science has driven significant business outcomes.
Strong understanding of A/B testing, experimental design, and causal inference techniques.
Experience with MLOps practices, including model deployment, monitoring, and lifecycle management in production environments.
Reside within the Detroit area or nearby, with the ability to work in a hybrid environment and regularly commute to our Detroit office as needed.

Responsibilities

Lead the design, development, and implementation of advanced machine learning models and algorithms to solve complex business problems.
Collaborate with cross-functional teams, including product managers, engineers, and business stakeholders, to identify data-driven opportunities and translate them into actionable insights.
Analyze large datasets to extract meaningful patterns, trends, and relationships, leveraging statistical methods, machine learning techniques, and data visualization tools.
Develop and validate approaches, ensuring accuracy, robustness, and scalability for deployment in production environments.
Communicate findings and recommendations to both technical and non-technical audiences through detailed reports, presentations, and data visualizations.
Mentor and provide guidance to junior data scientists and analysts, fostering a culture of continuous learning and innovation.