Product Owner (Data Science & Machine Learning within Fraud)



Software Engineering, Accounting & Finance, Product, Data Science
London, UK
Posted on Friday, October 20, 2023

Russian hacker, Vladimir Leonidovitch Levin, attempted the biggest bank heist the world had ever seen via dial-up internet in 1994, Zia Hayat, Callsign CEO and founder, was hooked - armchair fraud became a real possibility. From this moment, Zia knew he wanted to play a part in stopping the bad guys and securing the internet for all. Founded In 2012, Callsign's mission has been to make Digital Identity simple and secure for everyone and everything. In that time, we've grown to over 200 employees, opened offices in Singapore and Abu Dhabi, been recognised as a WEF Global Innovator and our technology is being used by many of the world's leading financial institutions to keep millions of consumers safe.

But we aren't stopping here. The identity revolution has only just begun, and we are looking to hire the brightest and inquisitive minds to help us make every web, mobile and physical Interaction seamless and secure. If this sounds like you, lets chat.

Domain Expert:

Be the domain and product subject matter expert for Fraud prediction and Identity assurance statistical modeling methods

Build upon knowledge of fraud methods and formalize the development of predictive models that meet the needs of our customers and help detect fraud across a wide range of security and fraud use cases including account takeover, account opening fraud, social engineering, bad actor behaviors

Inversely specify and design predictive models that assess the likelihood of positive user identification (a returning user is who they say they are) in the area of passive behavioral authentication, identity scoring, and fraud false positive management

Build upon knowledge of fraud and security mitigations to help protect against fraud by working with other product owners to develop customer protection and intervention products e.g. multi-factor authentication, risk-based authentication, and dynamic in-channel messaging


As a Product Owner take responsibility for product-led data science and machine learning engineering team

Work closely with the Head of Product and other Intelligence domain product owner(s) to define a product vision and own an internal and externally facing Roadmap to achieve landmark objectives

Lead the planning of product release plans and give clear goals to the team against measurable product objectives

Manage inbound customer feature requests on the backlog and roadmap

Manage inbound defects and incidents on the backlog

Prioritize against business value and defined strategy

Product-Led Data Science and ML Engineering

Provide vision and direction to data scientists and machine learning engineers

Create requirements to ensure clear and understandable user stories and acceptance criteria for all development

Ensure your team has an adequate amount of prior prepared tasks to work on to ensure continuous value-add

Own model development life-cycle and ML platform backlog assessing value (strategy), developing use cases (design), prioritizing stories, epics, themes, and owning scope (backlog management). All the time focusing on delivering the best experiences and maximum value

Engage with the wider Company to facilitate internal ideas and recommendations for product enhancements

Control Contributions:

Lead methods of continuous evaluation of model efficacy (statistical performance and reporting) across key metrics

Work with our security and data privacy teams with regard to the design and application of AI Ethics and Data Governance within the team

Strategy Contribution:

Support research and market analysis to ensure our Product Strategy and Roadmap are aligned

Follow our competitors and wider industry changes

Essential Skills and Experience (Technical):

You have a demonstrable understanding of fraud patterns and methods

You are proficient in SQL data exploration and Python-based software development e.g. as a fraud analyst, data scientist etc.

History of data-based product development e.g. machine learning, deep learning, statistics

Experience in the model development lifecycle and design including hypothesis capture, feature engineering, hypothesis proving, statistical performance review, and programmatic validation (functional/non-functional testing)

Essential Behavioral Skills:

Strong leadership with sound communication and presentation skills

Sound analytical and problem-solving skills; comfortable working within problem areas with uncertainty.

Demonstrate integrity, a positive attitude, and a passion for excellence.

Desirable Skills:

5+ years of technical experience as an ML Engineer or Data Scientist and looking to shape product development

Knowledge, experience and/or engagement with industry bodies and relevant standards and areas e.g. ISO, NIST

Familiar with AWS cloud services as an operating environment for data science

Hybrid working

Personal learning allowance

25 days holiday plus Callsign Holiday

Private Medical Insurance