Data Scientist at Lendi Group
Melbourne, Victoria, Australia -
Full Time


Start Date

Immediate

Expiry Date

16 Dec, 26

Salary

80000.0

Posted On

18 Sep, 26

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Industry

Information Technology & Services

Description

Job Description


  • Work with large datasets and feature store to gain insights, train predictive models and measure results.
  • Be involved in the full product life cycle.
  • Develop scalable and innovative ML solutions
  • Learn and implement latest AI and ML techniques.
  • Develop relationships with product managers and other stakeholders to influence business outcomes
  • Collaborate with the data team, reviewing solutions, sharing knowledge, and improving coding standards.
  • Collaborate with internal teams and stakeholders to gain a complete understanding of the problem to be solved and to implement the models to achieve desired outcomes.
  • Collaborate with external stakeholders.
  • Ensure projects are delivered on time and budget.
  • Ensure documentation of the proposed solutions.
  • Actively participate in improving ML Ops practices and standards

Responsibilities

Job Description


  • Work with large datasets and feature store to gain insights, train predictive models and measure results.
  • Be involved in the full product life cycle.
  • Develop scalable and innovative ML solutions
  • Learn and implement latest AI and ML techniques.
  • Develop relationships with product managers and other stakeholders to influence business outcomes
  • Collaborate with the data team, reviewing solutions, sharing knowledge, and improving coding standards.
  • Collaborate with internal teams and stakeholders to gain a complete understanding of the problem to be solved and to implement the models to achieve desired outcomes.
  • Collaborate with external stakeholders.
  • Ensure projects are delivered on time and budget.
  • Ensure documentation of the proposed solutions.
  • Actively participate in improving ML Ops practices and standards

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