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Senior Data Scientist
2 months ago
About the Role:
We are seeking a highly skilled Senior Data Scientist to join our team and drive the implementation of cutting-edge AI solutions in Risk Modelling and machine learning. The ideal candidate will have extensive experience in developing and deploying advanced AI models and techniques.
Key Responsibilities:
Lead the data science lifecycle, including data acquisition, cleaning, exploration,
feature engineering, and model training.
Develop and implement robust machine learning pipelines incorporating AI/ML and
Deep learning techniques, applying best practices for data pre-processing, model
selection, training, and evaluation for assessing creditworthiness and fraud potential.
Developing risk models: Creating ML models to evaluate financial risks associated
with lending or other financial activities.
Scoring algorithms: Designing and developing ML models to assess creditworthiness
or segment customers based on various factors.
Continuously monitor and evaluate model performance, identifying areas for
improvement and retraining as necessary.
Collaborate with engineers to integrate machine learning models into production
environments and ensure efficient deployment.
Stay current on the latest advancements in AI/ML and Generative AI by actively
researching new techniques and participating in training opportunities..
Requirements:
5+ years of experience in applied data science with a focus on machine learning
and financial modeling..
Experience with financial risk modeling or telecom scoring modeling. Knowledge of
credit risk assessment, fraud detection, or customer churn prediction
Proven track record of successfully designing, developing, and deploying machine
learning models in production environments.
Strong understanding of machine learning principles, algorithms, and frameworks
(e.g., scikit-learn, TensorFlow, PyTorch).
Proficiency in programming languages like Python, R, or Scala and familiarity with
data wrangling libraries (e.g., pandas).
Experience with cloud platforms (e.g., AWS, GCP, Azure) for data storage,
processing, and model deployment (a plus).
Strong communication and collaboration skills with the ability to explain complex
technical concepts to business.
A critical thinker with a problem-solving mindset and a passion for exploring new data
science and AI/ML techniques.
