Senior Data Scientist

August 7

Apply Now

Receive Emails with Similar Jobs

Zopa Bank

WebsiteLinkedInAll Job Openings

We’re Zopa Bank. Credit Cards | Loans | Savings

Fintech • tech • finance • loans • savings

201 - 500

💰 Venture Round on 2023-02

Description

• Lead high impact projects related to data and modelling, with a specific focus on Marketing and Customer Engagement. • Own the full lifecycle of your project, including the discovery of business opportunities through statistical analysis, data curation and processing, feature engineering, development of machine learning model, deployment to production and model monitoring. • Plan experiments and A/B Tests and use them to gather useful insights and inform the business strategy. • Engage with senior stakeholders across the company, influence critical business decisions, and make direct impacts on our products and millions of customers. • Work closely with product managers, analysts, data engineers and software engineers to make progress of your project. • Support other data scientists by knowledge sharing, code review, collaboration on common utilities and analytical infrastructure.

Requirements

• You love data. You are passionate about tackling real world problems with data. You have proven track record of solving complex data problem and deliver business value. • You are a scientist. Always curious and eager to learn. You have an inquisitive mind to delve under the surface and challenge status quo. You are fearless in innovation, for the good of our customers and the world. • You are a great communicator. You enjoy influencing decision makers with insights from data. You can foster mutual understanding and trust with stakeholders of different perspectives. • You are a team player, striving for the success of the team and collaborate with an open mind. You have the can-do attitude with strong commitment to get the job done. • You are proficient in SQL and have excellent Python skills, with a good understanding of the best practices in Software Engineering. • You have in-depth knowledge of machine learning algorithms (e.g. logistic regression, random forest, gradient boosted trees, neural networks, k-means, etc) and statistics (e.g., Monte Carlo, hypothesis testing, confidence intervals, maximum likelihood, bootstrap, Bayesian inference). • You have working knowledge of Git, Docker, CI/CD, REST API.