Senior Data Scientist - SMBC

SMBC: A trusted partner for the long term

Here at SMBC Group, we want to help you find the next step in your career so read on to discover if this opportunity is the one for you. We like to recognise potential in our people, so we welcome your application even when your experience doesn't perfectly align with the job description. Whilst we'll always strive to be better, we're proud of our inclusive culture, and encourage our applicants and colleagues to be their authentic, unique selves.

Who we are

United by a sense of purpose towards our customers - to be a trusted partner for the long-term - and our universal banking platform in EMEA, SMBC Group has an international growth agenda and award-winning products, meaning we provide exciting opportunities to work on a diverse range of projects and initiatives. We deliver a full suite of corporate finance products and solutions to our customers as well as investment banking and advisory services, and a range of innovative solutions in global capital markets. Read on to find out how you could enhance your skills and gain valuable experience, by joining us to support our clients transition to a sustainable future.

Role Summary

We are looking for aSenior Data Scientist to join the Data Analytics Team within the EMEA Data Management Office (DMO). This is an exciting opportunity to help develop and expand our data science capabilities, working closely with business and technology stakeholders to identify opportunities where advanced analytics and machine learning can deliver measurable value.The successful candidate will be a technically experienced, hands-on data scientist who enjoys solving complex business problems and translating ideas into practical analytical solutions. A key focus of the role will be developing proofs of concept to demonstrate feasibility and potential value of data science approaches, helping the organisation understand where these capabilities can improve processes, decision making and business outcomes.As our data science capability continues to evolve, the candidate will need to be comfortable working with ambiguity, taking initiative and exploring new approaches.

Accountabilities and Responsibilities:

• Identify and explore opportunities to apply data science, statistical modelling and machine learning techniques to solve business problems and deliver measurable value
• Design develop and evaluate hands-on proofs of concept to assess technical feasibility, effectiveness and potential business benefits of proposed analytical solutions
• Work closely with business stakeholders to understand challenges, identify suitable analytical approaches and translate business requirements into practical data science use cases
• Be able to work in world of siloed and disconnected data bringing context to the disparate views of similar data
• Undertake exploratory data analysis, data preparation, feature engineering and model development using appropriate programming languages, tools and analytical techniques
• Apply statistical analysis, predictive modelling, classification, natural language processing and other relevant techniques to address a range of business challenges
• Evaluate and communicate model performance, limitations, assumptions and potential risks, ensuring proposed solutions are appropriate for their intended business use
• Present technical findings and outcomes to both technical and non-technical stakeholders, clearly articulating potential business value and recommendations
• Support the development of data science capabilities across the Data Analytics function, through knowledge sharing, mentoring, technical guidance and practical upskilling of colleagues
• Help establish reusable analytical approaches, coding standards, documentation and best practices to support the effective and responsible use of data science
• Maintain awareness of emerging data science techniques, proactively identifying opportunities for their practical application within the organisation.

The anticipated salary range for this role is £84,000 - £126,000with the final offer determined based on the candidate's skills, experience, role scope, location, and relevant market factors. In addition to base salary, the role may be eligible for a discretionary incentive award and a competitive benefits package, including core benefits such as pension provision.

Business Area

The Data Analytics Function is one of five 'pillars' within the EMEA DMO which is part of the Operations Planning Department (OPPD). We are responsible for building out the Bank's data capabilities across all EMEA entities and all datasets.

The EMEA DMO initially concentrated on building foundational governance through improved Data Architecture, Data Management and Data Quality but is ultimately committed to exploiting data more effectively and innovatively across SMBC, to drive new ways of working and improved business outcomes. Our Data Strategy defines a vision for an aggregated and integrated data-enabled organisation that sets out the strategic outcomes to enable data driven decision making capability across the bank. We will continue to evolve the strategy while prioritising key foundational initiatives and business priorities for the next financial year.

We are driving data-led transformation through the bank, and it is a great opportunity to join us on this exciting journey.

Competencies

Essential experience:

Demonstrable hands-on experience working as a data scientist or in a similar advanced analytics role, with a track record of developing practical analytical solutions

Strong programming skills in Python, including experience using relevant data science and machine learning libraries

Practical experience applying statistical analysis, machine learning and predictive modelling techniques to real-world business problems

Experience developing proofs-of-concept, evaluating technical feasibility and demonstrating the potential business value of analytics approaches

Strong understanding of the end-to-end data science lifecycle, including data exploration, preparation, feature engineering, model development and evaluation

Demonstrate an understanding of the data life cycle and the evolution of data from raw value through to a meaningful data product

Ability to work independently in ambiguous or evolving environments, using initiative and sound judgement to identify appropriate solutions

Strong analytical and problem-solving skills, including the ability to translate complex business challenges into structured analytical approachesEffective written and verbal communication skills, including the ability