Data Science Engineer

At Quest Global, it’s not just what we do but how and why we do it that makes us different. With over 25 years as an engineering services provider, we believe in the power of doing things differently to make the impossible possible. Our people are driven by the desire to make the world a better place—to make a positive difference that contributes to a brighter future.

We bring together technologies and industries, alongside the contributions of diverse individuals who are empowered by an intentional workplace culture, to solve problems better and faster.

• Collaborate with data and subject matter experts and customer teams to seek, understand, validate, interpret, and correctly use data and business insights
• Train, validate and deploy machine learning pipelines
• Test, troubleshoot, and enhance customer software applications with and on behalf of customers
• Identify application performance bottlenecks and implement optimizations
• Write application specifications, tutorials and documentation

We are known for our extraordinary people who make the impossible possible every day. Questians are driven by hunger, humility, and aspiration. We believe that our company culture is the key to our ability to make a true difference in every industry we reach. Our teams regularly invest time and dedicated effort into internal culture work, ensuring that all voices are heard.

We wholeheartedly believe in the diversity of thought that comes with fostering a culture rooted in respect, where everyone belongs, is valued, and feels inspired to share their ideas. We know embracing our unique differences makes us better, and that solving the world’s hardest engineering problems requires diverse ideas, perspectives, and backgrounds. We shine the brightest when we tap into the many dimensions that thrive across over 21,000 difference-makers in our workplace.

• Experience in data science methods, including statistical analysis, machine learning, and data visualization.
• Experience identifying and resolving operational or data-related issues using documented procedures and prior case studies.
• Experience making small-scale system and process improvements to enhance functionality and efficiency.

• Applied Machine Learning experience (regression, classification, supervised, and unsupervised learning) with a strong mathematical foundation in linear algebra, calculus, probability, and statistics.
• Experience in time-series data analysis, including cleansing and normalization, and experience with scalable Machine Learning (Map Reduce, streaming).
• Software development expertise in Python and JavaScript, with experience using Git or other version control systems.
• Ability to drive projects independently and collaboratively, demonstrating a strong work ethic and commitment to organizational goals.