Synechron

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TECHNOLOGY Director of Data Science Toronto, Canada
Job Description

Reporting to Synechron’s Head of Data Science, the Director of Data Science - Canada will be responsible for building a market leading data science practice in Canada by partnering with Synechron’s Head of Canada and Head of Data Science to design, develop, and deliver cutting edge data science solutions to Canada’s leading financial institutions. The practitioner will architect, build, and sell innovative data science solutions incorporating Artificial Intelligence (AI) and Machine Learning (ML). The individual is expected to be a deep expert in data science who can support sales efforts, manage client engagements, lead teams, and be a hands-on developer of AI and ML solutions.

Responsibilities
  • Cultivate strong relationships with top level client decision makers and influence client buying behaviors based on Synechron’s Data Science capabilities, assets and thought leadership
  • Cultivate relationships with other Regional leadership teams and Synechron’s Client Account Leads to ensure that Synechron is delivering its best Data Science capabilities to the firm’s most complex and strategic accounts in Canada
Requirements

Execute Data Science Thought Leadership

  • Communicate Synechron’s thought leadership in AI and Data Science to clients and prospects throughout Canada, establishing Synechron as a thought leader in the Canadian Data Science market
  • Educate sophisticated clients on Data Science and how it can be applied to their financial services use cases
  • Provide ongoing feedback to the Head of Data Science on client feedback, market developments, competitive developments, and resource requirements
Basic Qualifications
  • A minimum of a Bachelor's degree in mathematics, statistics, engineering, data science, economics, and information management or related field of study
  • Experience communicating complex concepts to executives
  • A minimum of 5 years designing, implementing, and deploying full-stack scalable data science and machine learning solutions to solve business problems
  • A minimum of 5 years of experience building, designing, or developing large-scale data science infrastructure (Spark / Hadoop / Cloud) used to support the implementation of data science solutions and analyze diverse data sets
  • A minimum of 5 years working knowledge of data structures, algorithms, statistics, machine learning, natural language processing, and programming in Python or a related language
  • Demonstrated experience working in full-stack development teams to implement data science solutions at scale
Preferred Qualifications
  • Masters of PhD in Statistics, Computer Science, Artificial Intelligence or related field or an MBA with a strong quantitative and programming background
  • Experience developing data science solutions at scale for production systems
  • Experience translating stated business needs into problem statements, prototypes, and minimum viable products
  • Working knowledge of Apache Spark and Hadoop with experience developing data science solutions at scale using these and related platforms / frameworks (Kafka, Cassandra, Soir)
  • Experience developing and deploying machine learning solutions in a cloud environment (AWS, Azure, Google Cloud)
  • Deep theoretical and practical knowledge of machine learning, deep learning, statistical learning, statistics, probability, data visualization, and natural language processing
  • Experience managing complex data science projects including scoping, requirements gathering, resource estimations, sprint planning, and management of internal and external communication and resources
  • Sales or pre-sales experience
  • Ability to think quickly in client meetings to identify and communicate effective solutions to client problems spanning disciplines
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