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Machine Learning Engineer - Python - York (hybrid)

Candour Solutions
York
1 month ago
Applications closed

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Overview:

#TeamCandour are seeking a passionate and innovative Machine Learning Engineer / Data Scientist to join the team of our global financial services client out of their offices in York on a hybrid basis. If you have an entrepreneurial spirit and thrive in a dynamic environment, this could be the perfect opportunity for you.

Responsibilities:

Lead the development and implementation of innovative strategies to drive business growth
Identify new business opportunities and cultivate relationships with potential partners and clients
Collaborate with cross-functional teams to execute projects and initiatives
Analyse market trends and consumer behaviour to inform decision-making
Stay updated on industry developments and incorporate best practices into our business processes
Conduct market research and competitive analysis
Develop and execute marketing campaigns
Provide leadership and mentoring to team members
Utilize data analytics to drive business decisions

Key skills & qualifications:

Strong python programming skills
Good knowledge of software engineering best practice
Experience with TDD (pytest or equivalent)
Experience with cloud native deployments (currently in Databricks and Azure)
Experience with Databricks
Experience with managed endpoints, AKS or equivalent
Experience with VCS
Experience with CI/CD
Proven track record of driving business growth and achieving targets
Strong communication and negotiation skills
Ability to think creatively and strategically
Experience in project management and cross-functional collaboration
Knowledge of market research and analysis techniques
Proficiency in data analytics and business intelligence tools
Familiarity with digital marketing and social media strategies
Experience in strategic planning and execution
Strong leadership and team management skills

If you are ready to take on a new challenge and make a significant impact, we would love to hear from you!

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