Travelex

Lead Data Scientist

EUC Technical Engineer

Lead Data Scientist at Travelex in Mumbai, India. Requires expert-level data science and AI, Python with data science libraries, AWS experience, and SQL/NoSQL database proficiency.  Develop and implement data-driven solutions to enhance business decisions and product development.

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 Role Title - Lead Data Scientist Location - Mumbai, India Role Purpose As the Lead Data Scientist for Travelex, you will steer the discovery of the business insight hiding in our data. You will be designing, delivering and managing multiple work streams involving modelling, data mining, prediction, advanced analytics and AI. Your role is critical to the way we create Foreign Exchange and payment products based on deep understanding of our customers. Your work will continuously underpin important business decisions, working with product owners, data engineers, subject matter experts and managers across the company. You will be the colleague accountable for data science standards and deliverables across Travelex. This includes both hands-on technical work (such as statistical analysis and machine learning model development) and business-facing work (such as requirement gathering and prioritisation of requests). It also includes responsibility for underlying work such as data cleansing and documentation. Responsibilities Here are key things you’ll do as the Lead Data Scientist at Travelex. The list isn’t complete: as a competent data scientist, you’ll bring to Travelex your own ideas of what else is needed to become a world-class data-driven business. <ul><li>Liaise with business stakeholders to understand their analytical needs and convert it into data science tasks</li><li>Work with technical stakeholders to obtain relevant data and improve the data</li><li>Work with data engineers and analysts to agree data formats, prepare data for analysis and specify outputs</li><li>Use a wide range of machine learning techniques to explore data, extract insight from it, and train models</li><li>Use a wide range of statistical techniques to understand correlation and causation</li><li>Automate your work to create live tools, models, reports and dashboards</li><li>Undertake experiments of new AI techniques and use cases</li><li>Work with other data leaders (e.g. Head of Data Architecture, Data Intelligence Manager and Lead Data Engineer) to prioritise and plan work across the data teams</li><li>Provide line management, coaching and mentoring to more junior data scientists</li><li>Provide expertise in ML model training, validation, testing and release</li><li>Keep up-to-date with the rapid development of data science tools and techniques, and share this knowledge with others</li><li>Enhance data collection procedures</li><li>Develop and automate processes for anomaly detection</li><li>Develop and automate processes for testing the performance of business processes such as marketing campaigns</li><li>Create new ways to test the integrity and quality of our data</li><li>Present your analysis and the conclusions from it to stakeholders in a clear manner </li></ul>
Requirements Below are key requirements from our Lead Data Scientist. You don’t need to tick every box: success in our team is not limited to a fix list, but also depends on what else you bring with you. <ul><li>Expert level in data science and AI, including models, algorithms, libraries and toolkits</li><li>Significant hands-on experience with Python and the common data science Python libraries</li><li>Significant experience with data science on AWS</li><li>Proficiency in querying SQL and NoSQL databases</li><li>Ability to explain complex issues in simple terms</li><li>Good ability to present insight graphically to maximise clarity</li><li>Excellent analytical and problem-solving skills</li><li>An engaging, motivating and supportive team player</li><li>The ability to learn new tools, languages and methods quickly.</li><li>Good understanding wider concerns such as security and compliance</li><li>The curiosity to understand the business, its requirements and culture</li><li>Enjoys staying up-to-date with the latest advancements in data science, exploring new techniques, tools, and methodologies, and implementing them to improve existing processes.</li></ul>

 
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