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Vice President - Data Scientist Lead (Individual Contributor)

at J.P. Morgan

Back to all Data Science / AI / ML jobs
J.P. Morgan logo
Bulge Bracket Investment Banks

Vice President - Data Scientist Lead (Individual Contributor)

at J.P. Morgan

Mid LevelNo visa sponsorshipData Science/AI/ML

Posted 11 days ago

No clicks

Compensation
Not specified

Currency: Not specified

City
Manila
Country
Philippines

Lead end-to-end data science initiatives across the full lifecycle from data acquisition to model deployment in a VP-level role. Independently own projects, collaborate with stakeholders to translate business objectives into technical solutions, and deploy robust machine learning models. Communicate insights to senior leadership through clear visualizations and reports, ensuring scalability and reproducibility in production. Stay current with industry trends and drive strategic analytics initiatives as an individual contributor.

Location: Metro Manila, National Capital Region, Philippines

Unlock your potential as a Vice President – Data Scientist, owning the full data science lifecycle from data acquisition to model deployment. Join our innovative team to deliver impactful solutions that shape business strategy and drive operational excellence. Make your mark by transforming complex data into actionable insights and scalable models. Bring your expertise to a collaborative environment focused on growth, learning, and strategic influence.

Job Summary:
As a Vice President – Data Scientist, you independently lead end-to-end data science initiatives, from understanding business needs to deploying robust machine learning models. You collaborate with stakeholders to define requirements, acquire and prepare data, develop and validate models, and communicate insights that inform strategic decisions. You ensure solutions are scalable, reproducible, and aligned with organizational objectives, driving innovation and measurable business impact.

Job Responsibilities:

  • Own the full data science lifecycle, including data acquisition, preparation, modeling, validation, and deployment
  • Analyze complex datasets to uncover trends, patterns, and actionable insights
  • Design, develop, and implement machine learning models to solve business challenges
  • Collaborate with stakeholders to translate business objectives into technical solutions
  • Validate model performance and ensure scalability in production environments
  • Communicate findings and recommendations through clear visualizations and reports
  • Support data engineering efforts to maintain data quality and integrity
  • Document processes, methodologies, and model outcomes for transparency and reproducibility
  • Stay current with industry trends and emerging technologies in data science
  • Present technical concepts and results to senior leadership and non-technical audiences
  • Lead strategic analytics projects as an individual contributor

Required qualifications, capabilities, and skills:

  • Five years of experience in data science or a related field
  • Proven experience managing end-to-end data science projects
  • Proficiency in Python and/or R for data analysis and modeling
  • Experience with machine learning frameworks such as scikit-learn, TensorFlow, or PyTorch
  • Strong understanding of statistical analysis and data mining techniques
  • Experience with data visualization tools such as Tableau, Power BI, or matplotlib
  • Familiarity with cloud platforms (AWS, Azure, or GCP) for model deployment
  • Knowledge of data engineering concepts and relational databases
  • Excellent problem-solving and analytical skills
  • Strong communication skills to present technical concepts to non-technical audiences
  • Bachelor’s degree in Data Science, Computer Science, Statistics, or a related field

Preferred qualifications, capabilities, and skills:

  • Master’s degree in Data Science, Computer Science, Statistics, or a related field
  • Experience with big data technologies such as Spark or Hadoop
  • Background in deploying models in production environments
  • Experience working in Agile teams
  • Knowledge of MLOps practices
  • Industry certifications in data science or machine learning
  • Experience presenting to senior leadership
Lead end-to-end data science projects, delivering advanced analytics and machine learning solutions that drive business transformation.

Vice President - Data Scientist Lead (Individual Contributor)

at J.P. Morgan

Back to all Data Science / AI / ML jobs
J.P. Morgan logo
Bulge Bracket Investment Banks

Vice President - Data Scientist Lead (Individual Contributor)

at J.P. Morgan

Mid LevelNo visa sponsorshipData Science/AI/ML

Posted 11 days ago

No clicks

Compensation
Not specified

Currency: Not specified

City
Manila
Country
Philippines

Lead end-to-end data science initiatives across the full lifecycle from data acquisition to model deployment in a VP-level role. Independently own projects, collaborate with stakeholders to translate business objectives into technical solutions, and deploy robust machine learning models. Communicate insights to senior leadership through clear visualizations and reports, ensuring scalability and reproducibility in production. Stay current with industry trends and drive strategic analytics initiatives as an individual contributor.

Location: Metro Manila, National Capital Region, Philippines

Unlock your potential as a Vice President – Data Scientist, owning the full data science lifecycle from data acquisition to model deployment. Join our innovative team to deliver impactful solutions that shape business strategy and drive operational excellence. Make your mark by transforming complex data into actionable insights and scalable models. Bring your expertise to a collaborative environment focused on growth, learning, and strategic influence.

Job Summary:
As a Vice President – Data Scientist, you independently lead end-to-end data science initiatives, from understanding business needs to deploying robust machine learning models. You collaborate with stakeholders to define requirements, acquire and prepare data, develop and validate models, and communicate insights that inform strategic decisions. You ensure solutions are scalable, reproducible, and aligned with organizational objectives, driving innovation and measurable business impact.

Job Responsibilities:

  • Own the full data science lifecycle, including data acquisition, preparation, modeling, validation, and deployment
  • Analyze complex datasets to uncover trends, patterns, and actionable insights
  • Design, develop, and implement machine learning models to solve business challenges
  • Collaborate with stakeholders to translate business objectives into technical solutions
  • Validate model performance and ensure scalability in production environments
  • Communicate findings and recommendations through clear visualizations and reports
  • Support data engineering efforts to maintain data quality and integrity
  • Document processes, methodologies, and model outcomes for transparency and reproducibility
  • Stay current with industry trends and emerging technologies in data science
  • Present technical concepts and results to senior leadership and non-technical audiences
  • Lead strategic analytics projects as an individual contributor

Required qualifications, capabilities, and skills:

  • Five years of experience in data science or a related field
  • Proven experience managing end-to-end data science projects
  • Proficiency in Python and/or R for data analysis and modeling
  • Experience with machine learning frameworks such as scikit-learn, TensorFlow, or PyTorch
  • Strong understanding of statistical analysis and data mining techniques
  • Experience with data visualization tools such as Tableau, Power BI, or matplotlib
  • Familiarity with cloud platforms (AWS, Azure, or GCP) for model deployment
  • Knowledge of data engineering concepts and relational databases
  • Excellent problem-solving and analytical skills
  • Strong communication skills to present technical concepts to non-technical audiences
  • Bachelor’s degree in Data Science, Computer Science, Statistics, or a related field

Preferred qualifications, capabilities, and skills:

  • Master’s degree in Data Science, Computer Science, Statistics, or a related field
  • Experience with big data technologies such as Spark or Hadoop
  • Background in deploying models in production environments
  • Experience working in Agile teams
  • Knowledge of MLOps practices
  • Industry certifications in data science or machine learning
  • Experience presenting to senior leadership
Lead end-to-end data science projects, delivering advanced analytics and machine learning solutions that drive business transformation.