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Starling is the UK's first and leading digital bank on a mission to fix banking! Our vision is fast technology, fair service, and honest values. All at the tap of a phone, all the time.
We're a fully licensed UK bank with the culture and spirit of a fast-moving, disruptive tech company. We employ more than 3,000 people across our London, Southampton, Cardiff and Manchester offices.
Our technologists are at the very heart of Starling and enjoy working in a fast-paced environment that is all about building things, creating new stuff, and disruptive technology that keeps us on the cutting edge of fintech. We operate a flat structure to empower you to make decisions regardless of what your primary responsibilities may be. Help is never far away in our open culture; you will find support in your team and from across the business.
The way to thrive and shine within Starling is to be a self-driven individual and be able to take full ownership of everything around you: From building things, designing, discovering, to sharing knowledge with your colleagues and making sure all processes are efficient and productive to deliver the best possible results for our customers. Our purpose is underpinned by five Starling values: Listen, Keep It Simple, Do The Right Thing, Own It, and Aim For Greatness.
Hybrid Working We have a Hybrid approach to working here at Starling - our preference is that you're located within a commutable distance of one of our offices so that we're able to interact and collaborate in person.
Our Data Environment Our Data teams are aligned to divisions covering Banking Services & Products, Customer Identity & Financial Crime, and Data & ML Engineering. Our Data teams are excited about delivering meaningful and impactful insights to both the business and our customers.
Responsibilities:
You will be part of a team delivering data driven solutions and insights to improve the speed, efficiency, and quality of decision-making.
Work proactively with technical and non-technical teams to deliver insights to support the wider business.
Build, test and deploy machine learning models which will improve and/or automate decision making.
Provide insightful analytics across the bank to assist with decision making.
Engage with Engineering teams to ensure we capture data points that are relevant and useful for insights and modelling.
Requirements We're open-minded when it comes to hiring and we care more about aptitude and attitude than specific experience or qualifications. We think the ideal candidate will encompass most of the following:
Demonstrable industry experience Data Science/Machine Learning in one or more of:
Financial Crime
Anti-money laundering
Transaction monitoring
Anomaly detection
Excellent skills in Python and SQL.
Experience with libraries such as Scikit-learn, Tensorflow, Pytorch.
Strong data wrangling skills for merging, cleaning and sampling data.
Strong data visualisation and communication skills are essential.
Understanding of the software development life cycle and experience using version control tools such as git.
Demonstrable experience deploying machine learning solutions in a production environment.
Desirables:
Experience with AWS/GCP.
Desire to build explainable ML models (using techniques such as SHAP).
Interview process Interviewing is a two-way process and we want you to have the time and opportunity to get to know us, as much as we are getting to know you! Our interviews are conversational and we want to get the best from you, so come with questions and be curious. In general, you can expect the below, following a chat with one of our Talent Team:
Stage 1 - 30 mins with one of the team.
Stage 2 - Take home challenge.
Stage 3 - 90 mins technical interview with two team members.
Stage 4 - 45 min final with an executive and a member of the people team.
Benefits
25 days holiday (plus take your public holiday allowance whenever works best for you).
An extra day's holiday for your birthday.
Annual leave is increased with length of service, and you can choose to buy or sell up to five extra days off.
16 hours paid volunteering time a year.
Salary sacrifice, company enhanced pension scheme.
Life insurance at 4x your salary & group income protection.
Private Medical Insurance with VitalityHealth including mental health support and cancer care.
Generous family-friendly policies.
Perkbox membership giving access to retail discounts, a wellness platform for physical and mental health, and weekly free and boosted perks.
Access to initiatives like Cycle to Work, Salary Sacrificed Gym partnerships, and Electric Vehicle (EV) leasing.
About Us Starling Bank is an equal opportunity employer, and we're proud of our ongoing efforts to foster diversity & inclusion in the workplace. Individuals seeking employment at Starling Bank are considered without regard to race, religion, national origin, age, sex, gender, gender identity, gender expression, sexual orientation, marital status, medical condition, ancestry, physical or mental disability, military or veteran status, or any other characteristic protected by applicable law.
#J-18808-Ljbffr
Starling is the UK's first and leading digital bank on a mission to fix banking! Our vision is fast technology, fair service, and honest values. All at the tap of a phone, all the time.
We're a fully licensed UK bank with the culture and spirit of a fast-moving, disruptive tech company. We employ more than 3,000 people across our London, Southampton, Cardiff and Manchester offices.
Our technologists are at the very heart of Starling and enjoy working in a fast-paced environment that is all about building things, creating new stuff, and disruptive technology that keeps us on the cutting edge of fintech. We operate a flat structure to empower you to make decisions regardless of what your primary responsibilities may be. Help is never far away in our open culture; you will find support in your team and from across the business.
The way to thrive and shine within Starling is to be a self-driven individual and be able to take full ownership of everything around you: From building things, designing, discovering, to sharing knowledge with your colleagues and making sure all processes are efficient and productive to deliver the best possible results for our customers. Our purpose is underpinned by five Starling values: Listen, Keep It Simple, Do The Right Thing, Own It, and Aim For Greatness.
Hybrid Working We have a Hybrid approach to working here at Starling - our preference is that you're located within a commutable distance of one of our offices so that we're able to interact and collaborate in person.
Our Data Environment Our Data teams are aligned to divisions covering Banking Services & Products, Customer Identity & Financial Crime, and Data & ML Engineering. Our Data teams are excited about delivering meaningful and impactful insights to both the business and our customers.
Responsibilities:
You will be part of a team delivering data driven solutions and insights to improve the speed, efficiency, and quality of decision-making.
Work proactively with technical and non-technical teams to deliver insights to support the wider business.
Build, test and deploy machine learning models which will improve and/or automate decision making.
Provide insightful analytics across the bank to assist with decision making.
Engage with Engineering teams to ensure we capture data points that are relevant and useful for insights and modelling.
Requirements We're open-minded when it comes to hiring and we care more about aptitude and attitude than specific experience or qualifications. We think the ideal candidate will encompass most of the following:
Demonstrable industry experience Data Science/Machine Learning in one or more of:
Financial Crime
Anti-money laundering
Transaction monitoring
Anomaly detection
Excellent skills in Python and SQL.
Experience with libraries such as Scikit-learn, Tensorflow, Pytorch.
Strong data wrangling skills for merging, cleaning and sampling data.
Strong data visualisation and communication skills are essential.
Understanding of the software development life cycle and experience using version control tools such as git.
Demonstrable experience deploying machine learning solutions in a production environment.
Desirables:
Experience with AWS/GCP.
Desire to build explainable ML models (using techniques such as SHAP).
Interview process Interviewing is a two-way process and we want you to have the time and opportunity to get to know us, as much as we are getting to know you! Our interviews are conversational and we want to get the best from you, so come with questions and be curious. In general, you can expect the below, following a chat with one of our Talent Team:
Stage 1 - 30 mins with one of the team.
Stage 2 - Take home challenge.
Stage 3 - 90 mins technical interview with two team members.
Stage 4 - 45 min final with an executive and a member of the people team.
Benefits
25 days holiday (plus take your public holiday allowance whenever works best for you).
An extra day's holiday for your birthday.
Annual leave is increased with length of service, and you can choose to buy or sell up to five extra days off.
16 hours paid volunteering time a year.
Salary sacrifice, company enhanced pension scheme.
Life insurance at 4x your salary & group income protection.
Private Medical Insurance with VitalityHealth including mental health support and cancer care.
Generous family-friendly policies.
Perkbox membership giving access to retail discounts, a wellness platform for physical and mental health, and weekly free and boosted perks.
Access to initiatives like Cycle to Work, Salary Sacrificed Gym partnerships, and Electric Vehicle (EV) leasing.
About Us Starling Bank is an equal opportunity employer, and we're proud of our ongoing efforts to foster diversity & inclusion in the workplace. Individuals seeking employment at Starling Bank are considered without regard to race, religion, national origin, age, sex, gender, gender identity, gender expression, sexual orientation, marital status, medical condition, ancestry, physical or mental disability, military or veteran status, or any other characteristic protected by applicable law.
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