EMDec23-Risk-Data Scientist/Machine Learning Engineer

1 month ago

London, United Kingdom Workday Full time

Line of Service

Assurance

Industry/Sector

Not Applicable

Specialism

Risk

Management Level

Senior Associate

Job Description & Summary

Closing Date: 4pm 15 December

Qualification: No ACA qualification is required for this role

Location: London EP

About the team & role   

Enterprises will be leading the drive for growth and innovation across Risk, and enabling areas identified from within our business to have the space and breadth to rapidly scale. The purpose of our new BU is to incubate and scale some of our propositions and services to accelerate and supercharge their growth, as well as providing us with a place to develop some of our new solutions for the future.

We are currently made up of 4 key areas: Marketer & Media Owner, Sustainability, Enterprises Business Applications and Data Intelligence.

The Data Intelligence team helps our clients and their partners better understand their customers and how to serve them, by equipping them with the tools and insights to make informed, evidence based decisions. We currently serve clients predominantly in such industries as retail, leisure and hospitality, real estate and smart cities. 

Our team of industry experts, data and insights consultants, data scientists, data engineers and machine learning engineers use advanced analytics to uncover the rich profile of customers’ current and future behaviours to inform how clients can better serve and communicate with their customers.

Responsibilities  

We are seeking candidates with strong data science or machine learning engineering experience to deliver projects in the customer and front office domain.

Duties and responsibilities (dependent on the mix of data science and engineering):

  • Propose data science problem solving approaches

  • Co-create approaches to meet user needs with clients and colleagues

  • Prototype, test and improve new data science models

  • Work with colleagues to deploy your models, to document and present them to business users, and to retain ownership of them in production

  • Contribute to various aspects of the machine learning lifecycle for our market-facing products,  i.e. model deployment, monitoring and validation, and champion best practices for model testing

  • Help optimise the performance, architecture, and resilience of data science models and their deployment infrastructure

  • Gather requirements for new features and update stakeholders on progress

  • Continuously develop your own data science, machine learning and engineering skills, and help others to improve theirs

  • Contribute to the company's culture through code reviews and design discussions

  • Develop materials for assisting in client pitches

  • Engage in thought leadership activities

  • Contribute to the learning and development of colleagues

Essential skills and experience

Skills and experience (dependent on the mix of data science and engineering)

  • Experience providing advanced analytics (preferably, in a customer, retail & consumer, marketing or other front office context)

  • Professional record demonstrating business impact; domain experience in areas such as customer analytics, CRM, customer acquisition and retention, marketing effectiveness, consumer sentiment and retail businesses will be beneficial.

  • Excellent communication and presentation skills, including the ability to explain and present the findings of technical work to non-expert audiences

  • Fluency with Python machine learning and data science packages (pandas, scikit-learn, Apache, Spark, DASK, Tensorflow, etc.) or experience with programming languages and willingness to learn Python 

  • For engineering, experience in a DevOps role, ideally in a data science environment

  • Proven interest and technical expertise in data science, statistical modelling and/or machine learning

  • Knowledge around software concepts

  • Experience building and deploying data pipelines, e.g. in the context of ETL and machine learning applications

  • End to end project delivery

  • Proven ability to handle multiple project commitments simultaneously

  • Ability to define tasks clearly, estimating timings and efforts

  • Experience in collaborating with people with different expertise to orchestrate shared solutions

  • An ability and desire to learn new skills quickly

  • Academic background in a relevant quantitative field, e.g. statistics, engineering, computer science, with an advanced degree (PhD / MSc) in one of these disciplines preferred

  • For engineering, proficiency in testing, packaging and deployment in Python

Education (if blank, degree and/or field of study not specified)

Degrees/Field of Study required:

Degrees/Field of Study preferred:

Certifications (if blank, certifications not specified)

Required Skills

Optional Skills

Desired Languages (If blank, desired languages not specified)

Travel Requirements

Not Specified

Available for Work Visa Sponsorship?

Yes

Government Clearance Required?

No

Job Posting End Date

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