Intermediate Data Scientist

Summary

Join AlgaeCal as an Intermediate Data Scientist to develop mathematical algorithms and apply machine learning to analyze business data, test hypotheses, and translate raw information into actionable strategies. You will build predictive models, optimize AI applications, and refine data architectures. The ideal candidate possesses 2+ years of experience as a Data Scientist, strong coding skills in Python or R, expertise in SQL and relational databases, and a deep understanding of machine learning algorithms. You will work with large datasets, design data warehouses, and standardize data models. AlgaeCal offers above-market pay, monthly team events, flexible stat holidays, weekly team lunches, a casual dress code, a dog-friendly office, remote work options, and a positive team culture.

Requirements

• 2+ years experience as a Data Scientist (or a similar role)
• Serious coding skills in Python or R
• Expertise in SQL and relational databases
• Kaggle-level knowledge of artificial intelligence models
• A deep understanding of machine learning algorithms
• Hands-on experience with data warehouses
• A knack for standardizing and improving data models
• A laser-sharp eye for detail
• An entrepreneurial approach to data
• You’re humble—you put the team and others’ needs ahead of your own
• You’re hungry to learn more
• You’re people smart––in the sense that you’re a great teammate

Responsibilities

• Develop mathematical algorithms and apply machine learning to analyze business data, test hypotheses, and turn raw information into strategies that drive measurable results
• Build predictive models, optimize AI applications, and refine data architectures that have had a measurable impact
• Translate data into actionable insights that drive business decisions
• Build and refine machine learning models
• Use statistical modeling and data science tools to solve complex problems and unlock growth opportunities
• Write efficient queries and optimize data structures
• Work with large datasets, ensuring data is organized, accessible, and primed for analysis
• Design, maintain, and optimize scalable data storage solutions that support robust analytics
• Standardize and improve data models
• Work with data at scale, refining schemas and improving architectures to ensure efficiency, accuracy, and usability across the organization
• Spot trends, outliers, and opportunities
• Think strategically about how data can be leveraged to create business value
• Identify new ways AI and machine learning can drive efficiency, sales, and profitability

Preferred Qualifications

Industry know-how that adds value. If you’ve got experience in consumer packaged goods, e-commerce, or the health/supplement industry, that’s a huge plus

Benefits

• Monthly team events and activities
• Flexible Stat Holidays with the option to bank days for later use
• Weekly team lunches
• Casual dress code
• Incredible dog friendly, Yaletown office one block from SkyTrain
• Remote working is okay with us too