Trainee - Data Scientist

Synopsis of the role

What You’ll Do

• Developing and implementing statistical models and machine learning algorithms to predict credit risk, customer behavior, and fraud patterns.
• Collaborating with cross-functional teams to understand business requirements and translate them into actionable data insights.
• Performing exploratory data analysis, feature engineering, and model evaluation.
• Ensuring data quality and integrity through rigorous data cleaning and validation processes.
• Staying up-to-date with the latest advancements in data science and applying them to business problems.
  

What Experience You Need

• Statistical and Machine Learning Techniques: Proficiency in statistical modeling, machine learning algorithms (regression, classification, clustering, etc.), and their implementation.
• Data Manipulation and Analysis: Expertise in SQL, Python (or similar programming languages), and data manipulation tools (Pandas, NumPy) to extract, clean, and analyze large datasets.
• Problem-solving and Analytical Skills: Ability to break down complex problems, identify patterns, and draw meaningful conclusions from data.
• Communication Skills: Effective communication of technical concepts to both technical and non-technical audiences.
  

What Could Set You Apart

• Domain Knowledge: Understanding of the credit industry, risk modeling, and fraud detection is a significant advantage.
• Passion for Data: A genuine interest in exploring data, uncovering insights, and experimenting with new methodologies.
• Business Acumen: Ability to connect data insights to business outcomes and propose data-driven solutions.
• Innovation: A creative mindset to explore new approaches and technologies to solve complex problems.
• Team Collaboration: Strong interpersonal skills and the ability to work effectively in a collaborative environment.