Senior Specialist, Data Scientist (Credit Risk)

Job title:                                  Senior Specialist, Data Scientist (Credit Risk)

Location:                                London

Hours:                                     Full-time

Wage:                                     £65,000 - £70,000

Work Pattern:                       Monday – Friday

Employer:                              NewDay Cards Ltd      

Duration:                               Permanent

Date advert posted:              7 August 2019

Closing date:                         4 September 2019

Job description

NewDay is seeking a Senior Specialist, Data Scientist (Credit Risk) to join its London office.

Key responsibilities

The key responsibilities include:

• using advanced statistical and machine learning (ML) techniques to identify new trends and relationships in data;
• developing knowledge of all relevant data resources within NewDay, and in the Credit Industry;
• harvesting, wrangling and prototyping new data sources internally and external to NewDay to drive value for NewDay and our customers;
• mastering standard ML modelling algorithms and development methodologies;
• researching, testing and recommending new algorithms or products in the Data Science stack as these fast moving technologies develop, keeping NewDay at the forefront of innovation;
• presenting approach and output to stakeholders, adapting the level of detail as appropriate;
• governance: supporting the management of models through appropriate sign-off including selling the model into the business, support accurate and timely implementation of models developed including UAT, and full documentation of final models. Ensure effective scorecard monitoring is in place;
• leadership: providing mentoring support to junior analysts within the Decision Science team and help contribute to the wider team’s deliverables as well as own deliverables;
• partner management: enhancing relationships with internal and external partners to ensure effective feedback loop and execution of strategies;
• end to end Data Science products ownership; and
• managing projects to timelines and make recommendations on trade-offs.

Essential qualifications, skills and experience

The successful candidate must possess the following qualifications, skills and experience:

• MSc in data science related field (eg machine learning, statistics, mathematics, analysis);
• relevant hands on experience in machine learning, building datasets, selecting and engineering features, building and optimising algorithms;
• relevant experience applying Data Science to business problems (ideally credit) in a corporate environment;
• proficiency in machine learning techniques;
• proficiency with open source analytic coding including either Python or R;
• proficiency in statistical techniques;
• relevant experience in data visualisation and communication;
• relevant experience with statistics/machine learning packages;
• relevant experience in SQL/data manipulation skills required including cleaning and managing data; 
• analytical and problem solving skills;
• enthusiastic self learner keeping up with latest techniques, technology and market trends;
• passionate about modelling and other techniques to drive value from big data;
• personable, credible, with good communication skills;
• excellent interpersonal and written communication skills, with the ability to present ideas in business-friendly language;
• self-motivated, able to work in a high-pressure environment;
• strong organisational, planning and time management skills;
• ability to build strong and effective working relationships;
• ability to embrace company culture and embed into day-to-day interactions;
• strong sense of accountability and ownership;
• ability to adapt in an environment where priorities evolve;
• self starter and eager to learn and develop skills;
• strong sense of ownership and accountability;
• pragmatic; and
• team player.

To apply: please upload your CV and a cover letter directly through the portal.

Date posted: 7 August 2019

Closing date: 4 September 2019