Product Owner (Data Science & Machine Learning within Fraud)

Russian hacker, Vladimir Leonidovitch Levin, undertook the most colossal bank robbery the world had ever come across through dial-up internet back in 1994. This event enthralled Zia Hayat, the CEO and founder of Callsign, and he realized the reality of fraud executed from the comfort of one's living room. This was the moment Zia decided he wanted to play a role in combating the villains and making the internet safe for everyone. Established in 2012, the main aim of Callsign has been to simplify and fortify digital identities for everyone and everything. During this period, we have expanded to over 200 employees, opened branches in Singapore and Abu Dhabi, been acknowledged as a WEF Global Innovator, and our technology has been embraced by several of the world's leading financial bodies to safeguard numerous customers. However, our journey doesn't end here. The revolution of identity is just getting started and we are keen on hiring the most intelligent and curious minds to assist us in making every web, mobile and physical interaction smooth and secure. If this sounds like you, let's engage in a conversation. Requirements Domain Expert: You should be an expert on domain and product subject matters for Fraud prediction and Identity assurance statistical modeling procedures. Develop Your understanding of fraud techniques and formalize the creation of predictive models that cater to our clients' requirements and help detect fraud across a wide variety of security and fraud instances such as account takeover, account opening fraud, social engineering, bad actor behaviors. Clearly specify and design predictive models that assess the probability 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. Expand your knowledge of fraud and security countermeasures to help prevent fraud by collaborating with other product owners to develop customer protection and intervention products like multi-factor authentication, risk-based authentication, and dynamic in-channel messaging. Planning: As a Product Owner, undertake responsibility for product-led data science and machine learning engineering team. Work in close coordination with the Head of Product and other Intelligence domain product owner(s) to define a product vision and possess an internal and external facing Roadmap to accomplish landmark objectives. Lead the planning of product release plans and set clear targets to the team against measurable product objectives. Manage incoming customer feature requests on the backlog and roadmap. Handle inbound defects and incidents on the backlog. Prioritize based on business value and defined strategy. Product-Led Data Science and Machine Learning 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 always has a sufficient quantity of pre-prepared tasks to work on for continuous value-addition. 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). Continuously focus on delivering the best experiences and maximum value. Engage with the larger 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. Collaborate with our security and data privacy teams concerning 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. Keep track of our competitors and broader industry changes. Essential Skills and Experience (Technical): You possess a verifiable understanding of fraud patterns and techniques. You are skilled in SQL data exploration and Python-based software development, for example, as a fraud analyst, data scientist, etc. A history of data-based product development such as 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 accompanied by sound communication and presentation skills. Strong analytical and problem-solving skills; comfortable working with uncertainty in problem areas. Demonstrate integrity, a positive attitude, and a zeal 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, for example, ISO, NIST. Familiarity with AWS cloud services as an operating environment for data science. Benefits Hybrid working. Personal learning allowance. 25 days of leave plus Callsign Holiday. Private Medical Insurance.