Lead Data Scientist
Cairo, Cairo Governorate, Egypt
Applications have closed
About the job:
As Lead Data Scientist you are responsible for spearheading the predictive modeling and machine learning division of the data science department to facilitate growth, revolutionize processes and streamline our customer experience.
Responsibilties:
- 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.
Requirements
- Proven work experience as an end-to-end Data Scientist across diverse business domains (previous FinTech experience is a major plus).
- Ability to lead, motivate and organize team efforts through strong mentorship skills, technical prowess, and “2-steps ahead” business thinking.
- Solid understanding of mathematical and statistical modeling along with machine learning and AI algorithms (knowledge of Graph models and databases is a plus).
- Strong experience with data pre-processing methods and techniques.
- Robust experience with the machine learning cycle, from development and training to deployment and re-training.
- Knowledge of data mining and segmentation techniques.
- Expertise with cloud-based infrastructure (e.g. AWS or GCP).
- Expert capabilities with both SQL and Python, with an aptitude for data visualization
- Strong knowledge of MLOps
Benefits
- Competitive salary.
- Pension Plan scheme as per company policy.
- Premium Family medical insurance.
- Exclusive access to our circles with the ultimate credit limit and reserved 1st slots.
- Unlimited annual leave policy.
- Mentorship and career growth.
- Entrepreneurial working environment.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: AWS Classification Clustering CX Data analysis Data Mining Data visualization Deep Learning EDA Engineering Feature engineering FinTech GCP Machine Learning ML models MLOps Predictive modeling Python SQL Statistical modeling Statistics
Perks/benefits: Career development Competitive pay Medical leave Startup environment
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