Data Science Chapter Lead - Gaydon, United Kingdom - JLR

JLR
JLR
Verified Company
Gaydon, United Kingdom

2 weeks ago

Tom O´Connor

Posted by:

Tom O´Connor

beBee Recruiter


Description

REQ ID:
122307


JOB TITLE:
Data Science Chapter Lead


SALARY:
£66,000 - £75,000


POSTING END DATE:
07/03/2024


LOCATION:
Gaydon with occasional travel to London


Beyond Property, Purchasing, HR and IT, more than being part of our Finance or Marketing teams, beyond even Sales and Service, every role in every business area offers unique opportunities to make an impact on the future of mobility and the automotive industry.


WHAT TO EXPECT


JLR's Customer and Marketing Analytics teams are driving for continuous improvement on their existing machine learning models, and to find the perfect balance between innovation and business performance.

As a Data Science Chapter Lead, you will support and challenge the Product Owners in the creation of new models for best practises in utilising the latest techniques and tools and creating consistency within the models.


You will be working with the Product Owners and Data Engineering teams to create predictive and prescriptive Models to understand our customers behaviours better and predict their next moves.


Key Accountabilities and Responsibilities

  • Ensure all Customer and Marketing Analytics Models are set up inside an Governed MLOPS process that ensure performance is monitored
  • Advice on best practise for set up of new machine learning models working with the relevant group product owner within analytics
  • Ensuring all models are build in the most scalable way.
  • Work with Customer Data Group and Data Engineering Leads to deliver a robust feature set that can be consumed by multiple models and will allow models to be quickly scaled to multiple markets if successful.
  • Manage relationship with Central Data Science team to ensure Customer and Marketing Analytics team is aligned with global policies and procedures
  • Ensure all modelling is compliant with relevant legislation around privacy and bias.
  • Manage the allocation of graduate team members into product\project squads
  • Provide pastoral and profession development support to the graduates in data science growing their capabilities and find projects to challenge them and drive their development

WHAT YOU'LL NEED


As a Data Science Chapter Lead, we are looking for someone who is passionate about data science with a desire to be always learning and pushing the boundaries of development.


Essential:


  • Experience in endtoend of building machine learning models, embedding them in business process and with a MLOps Framework
  • Knowledge of Python, SQL and R and experience building machine learning models within Google Cloud Platform including Vertex AI
  • Advocate of the use of machine learning to drive operation excellence and marginal gains and able to convey this others in a clear way
  • Proven ability to drive deliver appropriate solution where data can be sparse and/or incomplete
  • Strong interpersonal/communication skills, including ability to manage relationships and communicate effectively at all levels.

SO WHY US?


Bring all this to the home of premium innovation, and you'll find the opportunities to further your career with a world-class team, a discounted car purchase and lease scheme for you and your family, membership of a competitive pension plan, private medical cover and performance related bonus scheme.

As a manager, you'll also be able to select one of our luxury premium vehicles to lease at a fraction of the cost.

All this and more makes JLR the perfect place to continue your journey.


This role may offer the opportunity for hybrid working where you can split your time between working from home and in the office.

At JLR, hybrid working is a voluntary, non-contractual arrangement providing employees with more choice and flexibility around how, when and where they work, if suitable for their role.

Further details can be discussed with the Hiring Manager at interview stage.

JLR is committed to equal opportunity for all.

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