Lead Data Scientist

ABOUT US

At Money Fellows we believe that there is only one way to build an outstanding organization; and that is to attract exceptionally talented people who are aligned with our mission, thrive on challenges and are passionate about problem-solving. Being a market leader in the digital FinTech space, we facilitate to our customers the easiest and fast digital financial solutions which can enhance their lives. We are operating now in Egypt with a clear vision towards expansion in the region. We aim to build an inspiring organization with an engaged and high-performing culture. Joining the team now would mean that you could have a direct impact on the company’s growth trajectory. If you are hungry to make an impact and develop your skills in a dynamic environment, collaborating with like-minded people, we want to hear from you.

ABOUT THE ROLE:

Key responsibilities include:

• • Analyze complex financial datasets: Lead the analysis of intricate financial datasets to identify patterns, trends, and correlations using statistical techniques and machine learning algorithms. 
  • Develop predictive models and algorithms: Drive the development of advanced predictive models and algorithms to forecast financial outcomes, detect anomalies, and support risk management and decision-making processes. 
  • Conduct exploratory data analysis: Lead the team in conducting exploratory data analysis to uncover valuable insights, generate hypotheses for further investigation, and guide strategic initiatives. 
  • Apply machine learning algorithms: Utilize a wide range of machine learning algorithms, including regression, classification, clustering, and deep learning, to solve complex business problems and enhance fintech applications. 
  • Train, validate, and optimize models: Lead the team in training, validating, and optimizing machine learning models using appropriate techniques, such as cross-validation, hyperparameter tuning, and feature selection. 
  • Collaborate with cross-functional teams: Work closely with software engineers, developers, and stakeholders to implement and deploy machine learning models into production environments, ensuring seamless integration and scalability. 
  • Communicate insights and recommendations: Prepare and deliver comprehensive presentations, reports, and dashboards to convey insights, findings, and recommendations to technical and non-technical audiences, influencing strategic decision-making. 
  • Data preparation and feature engineering: Lead the implementation of data cleaning, transformation, and feature engineering techniques to ensure high-quality data for analysis and modelling.