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Mid LevelFull-timePythonRustMachine LearningData ScienceAIMLNLP
Salary Range
$52,488 - $71,013 /year
This salary is estimated based on similar roles. The actual salary may vary.
About the Role
The Data Scientist will be responsible for building, testing, and deploying statistical and machine learning models to drive better understanding of customers, products, and operations. This role will design and develop effective data science solutions to solve complex business problems.
Key Responsibilities
- →Collaborate with data engineers, business intelligence analysts, and other stakeholders to deliver data science solutions
- →Lead the design, build, and deployment of data products including statistical and machine learning models
- →Develop project plans based on stakeholder requirements and provide updates to the data team
- →Maintain knowledge of machine learning and deep learning algorithms, and recommend their business applications
- →Liaise with Global data science teams for collaboration and adoption of new tools
- →Contribute to the development of the global ML Ops platform in Canada
Requirements
- ✓2-3 years experience in data science, data engineering, or relevant data disciplines
- ✓Experience identifying business opportunities for data science and ML solutions
- ✓Strong grasp of advanced statistical concepts and data science methodologies
- ✓Intermediate Python programming skills
- ✓Advanced SQL querying skills
- ✓Understanding of data visualization best practices and proficiency with BI Platforms
- ✓Strong analytical and problem-solving skills
- ✓Ability to communicate complex concepts to technical and non-technical stakeholders
- ✓Bachelor’s degree in STEM, Economics, or Business preferred
Benefits
- ★Box Discount - 75% discount on weekly HelloFresh and Chefs Plate meal kits
- ★Health & Wellness - Health & Dental benefits from day 1
- ★Vacation & PTO - Generous vacation and PTO
- ★Family Benefits - Parental leave top-up program
- ★Growth & Development - Career progression support
- ★Flexible Hybrid work approach with minimum 2 days in office per week
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