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Lead Data Scientist

  • Toronto, ON, Canada

Full-time

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Job details

Job type
Full-time
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Experience
At least 7 to 10 years of proven experience in developing and deploying Machine learning and Deep learning solutions end-to-end (data exploration to deployment).
Posting language
English
Posted

Original job description

Job title: Lead Data Scientist

Location: 121 Bloor st E, Toronto, Canada (5days onsite)

Summary: Our Purpose - We work to connect and power an inclusive, digital economy that benefits everyone, every where by making transactions safe, simple, smart and accessible. Using secure data and networks, partnerships and passion, our innovations and solutions help individuals, financial institutions, governments and businesses realize their greatest potential. Our decency quotient, or DQ, drives our culture and everything we do inside and outside of our company. We cultivate a culture of inclusion for all employees that respects their individual strengths, views, and experiences. We believe that our differences enable us to be a better team one that makes better decisions, drives innovation and delivers better business results.

Job Description Responsible for developing, deploying, and monitoring Data Science solutions that involve Machine Learning, Deep Learning, GenAI, Agentic and other AI techniques.

Responsibilities

  • Transform complex business challenges into scientific research problems
  • Develop data-driven solutions to address business challenges using appropriate techniques (AI, ML, DL, GenAI etc.)
  • Hands on data extraction, data analysis, data cleaning, preparation, modeling, and evaluation.
  • Conduct data analysis to support business cases, prove hypotheses, new ideas and proof of concepts.
  • Build and execute various data science projects for product and business use cases across the organization.
  • Deploy, document, maintain and monitor the developed solutions
  • Presenting data science results to a variety of audience
  • Protect the developed algorithms and solutions by patenting the technology and consider publishing at academic and industrial research conference.
  • Build prototypes and proof-of-concepts and conduct tool evaluations.
  • Lead projects independently end-to-end.
  • Knowledge dissemination by presenting work externally at conferences and Universities.
  • Collaborate with internal teams and across other Mastercard teams

All About You

  • At least 7 to 10 years of proven experience in developing and deploying Machine learning and Deep learning solutions end-to-end (data exploration to deployment). Will consider even 5+ years if candidate has a Ph.D. from relevant areas.
  • Deep understanding of different Machine learning, Deep learning, GenAI and AI algorithms and the math behind it.
  • Strong scientific communication skills.
  • Handling data responsibly by maintaining data governance, privacy, and other standards
  • Curious, Critical thinker, good hacking skills and scientific reasoning.
  • Not afraid to ask questions and propose new ideas
  • Proactive in presenting contributions to diverse audiences and stakeholders.
  • Experience in building GenAI based solutions using LLM, SML, RAG, VectorDBs, and agentic frameworks.
  • Master s in computer science or quantitative field is a must, and PhD is good to have.

Skills

Python, PySpark, SQL

ML Frameworks, Deep Learning Frameworks, Agentic Frameworks

Databricks, Hadoop, AWS/Azure.
More about this job

Responsibilities

The Lead Data Scientist is responsible for developing, deploying, and monitoring Data Science solutions using various AI techniques. This includes transforming business challenges into scientific research problems and building data-driven solutions.

Requirements

Candidates should have at least 7 to 10 years of experience in developing and deploying machine learning and deep learning solutions, with a strong understanding of relevant algorithms. A Master's degree in computer science or a quantitative field is required, with a Ph.D. preferred.

Skills

  • Python
  • PySpark
  • SQL
  • Machine Learning
  • Deep Learning
  • GenAI
  • AI
  • Data Analysis
  • Data Cleaning
  • Data Preparation
  • Data Modeling
  • Data Governance
  • Hadoop
  • AWS
  • Azure
  • Databricks

Visa sponsorship

Not detected in the job text

Categories

  • Technology
  • Data & Analytics
  • Engineering

Keywords

  • Data Scientist
  • Machine Learning
  • Deep Learning
  • GenAI
  • AI
  • Data Science
  • Data Analysis
  • Data Cleaning
  • Data Preparation
  • Data Modeling
  • Data Governance
  • Python
  • PySpark
  • SQL
  • Hadoop
  • AWS
  • Azure
  • Databricks

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