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Data Scientist At BoxyCharm


Toronto, On

Job Description


Boxy Charm is seeking a highly motivated individual responsible for driving intelligent solutions and recommendations for the company.

The Data Scientist will use a range of data science and machine learning methodologies to build solutions for a variety of business initiatives. Additionally, the ideal candidate will be able to solve complex problems and apply those solutions within a cutting-edge cloud-based technology platform.

The role will be filled with a solution-oriented candidate that thrives on working in a highly dynamic and engaging environment.

Essential Duties and Responsibilities

  • Work closely with different business units and translate high level business problems into actionable deliverables for the Data & Algorithms team
  • Work with a wide variety of data ranging between social media and email to customer transactions and logistics
  • Develop a variety of machine learning models including customer recommendations, customer propensity, forecasting, and marketing performance.
  • Collaborate closely with the Software Development and DevOps teams to ensure continued delivery of high quality data through our data processing pipeline
  • Partner with various business stakeholders and implement solutions that improve their business process
  • Conduct big data analysis using SQL, Python, Snowflake, Spark and other technologies
  • Break down complex projects and problems into actionable tasks that be delivered quickly and iteratively and provide value to the business stakeholders

Key Understandings

  • Customer lifetime value, regression analysis, cohorts, retention, customer lifecycle, customer segmentation, machine learning, large-scale data analysis, classification and propensity modeling

Education and/or Experience

  • Bachelor’s degree or higher in Computer Science, Math, Statistics or a related field
  • 3+ years of experience programming in languages such as Python, Java, Scala, Ruby, R
  • 3+ years of experience working with SQL and relational databases
  • 3+ years of experience with machine learning, statistical modeling, and data mining techniques
  • Experience with one or more machine learning algorithms such as neural networks, regression, clustering etc.
  • Working experience with machine learning technologies such as TensorFlow, Keras, ScikitLearn,, MXNet, Caffe, Gluon etc. is highly desirable
  • Experience working in an Agile (SCRUM, XP etc.) development environment
  • Experience with AWS or other cloud environments is desirable
  • Knowledge of Big Data and NoSQL systems such as Snowflake, Hadoop, Spark, MongoDB, etc. is a plus

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