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Data Scientist - Jobs in Toronto

NearSource
Job LocationToronto
EducationNot Mentioned
SalaryNot Mentioned
IndustryNot Mentioned
Functional AreaNot Mentioned
Job TypeContract

Job Description

Take on the role of Data Scientist for a multinational Fortune 500 Project in Canada. Drive innovation and contribute to technological excellence. Apply today to become a key player in the dynamic team.Responsibilities:

  1. Tackle diverse challenges to gain insights into customer interactions with the company #39;s products, identifying key drivers for increased adoption and engagement.
  2. Utilize expertise in quantitative analysis, data mining, and machine learning to develop models that guide product development, strategic decision-making, and roadmap prioritization.
  3. Design and implement machine learning pipelines to enhance the products evidence-based decision-making capabilities.
  4. Collaborate closely with senior leaders across Product, Marketing, Engineering, and Design teams to ensure data-driven decisions are made using the most impactful data science and analytics methodologies.
  5. Provide technical leadership and mentorship to junior team members, helping them deliver key machine learning-powered features for the Digital Customer Platform.
Minimum Qualifications:
  1. MS or PhD in a quantitative discipline such as Mathematics, Physical Sciences, Statistics, Computer Science, or a related field.
  2. 5+ years of industry experience with a strong passion for designing, analyzing, and deploying machine learning solutions.
  3. Expertise in Large Language Models (LLMs), including RAG and Generative AI, as well as Natural Language Processing (NLP).
  4. Experience with relational (SQL) and/or NoSQL databases.
  5. Hands-on experience with big data technologies like Hadoop, Spark, and Hive.
  6. Proficient in one or more programming languages such as Python, Java, or Scala.
  7. Skilled in using data science toolkits such as pandas, Jupyter, scikit-learn, and TensorFlow.
  8. Familiarity with machine learning techniques including classification, clustering, regularization, optimization, and dimensionality reduction.
  9. Ability to write clean, well-documented, scalable code, with Python being the preferred language.
  10. Strong communication skills, capable of translating complex technical concepts for non-technical audiences and effectively presenting data insights.
  11. Experience with cloud platforms, particularly AWS.
  12. Familiarity with MLOps practices and optimizing machine learning workflows in production.
  13. Proven track record in leading research that results in published work.!NearSource Technologies values diversity and is committed to equal opportunity. All qualified applicants will be considered regardless of their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as protected veterans.

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