Indicina Technologies Limited Recruitment for Data Science Intern
Indicina Technologies Limited is building the ML-driven credit infrastructure Africa needs to drive economic inclusion on the continent. It is a global team with deep domain and technical expertise passionate about building the future of digital financial services.
We are recruiting to fill the position below:
Job Position: Data Science Intern
Job Location: Lagos
Employment Type: Full-time
About the Role
- As a Data Science Intern, you will have the opportunity to gain hands-on experience in the field of credit risk assessment and contribute to real-world projects.
- You will work closely with experienced data scientists and analysts to analyze data, develop models, and help us make data-driven decisions in the credit domain.
Job Responsibilities
- Assist in the collection, cleaning, and exploratory analysis of credit-related datasets to identify trends, patterns, and insights.
- Collaborate with data scientists to develop and fine-tune credit risk models, including machine learning and statistical models.
- Create data visualizations and dashboards to communicate results and insights effectively to stakeholders.
- Document your work, including data preprocessing steps, model development processes, and key findings, for knowledge sharing and future reference.
- Stay updated with the latest developments in data science and credit risk assessment and propose innovative solutions to enhance our credit risk modeling efforts.
- Support model validation efforts by conducting performance evaluation, model testing, and validation exercises.
- Help identify and engineer relevant features from diverse data sources to enhance model accuracy and predictive power.
- Work closely with cross-functional teams, including data engineers, business analysts, and risk management professionals, to understand business requirements and contribute to solving complex credit-related challenges.
Required Experience and Qualifications
- Strong analytical and problem-solving skills.
- Proficiency in programming languages such as Python or R.
- Basic knowledge of machine learning algorithms and statistical methods.
- Relevant coursework or projects related to data analysis, machine learning, or credit risk modeling.
- Experience with data science libraries and frameworks (e.g., scikit-learn, TensorFlow, PyTorch) is a plus.
- Familiarity with data manipulation libraries (e.g., pandas, numpy) and data visualization tools (e.g., Matplotlib, Seaborn).
- Excellent communication and teamwork skills.
- A strong desire to learn and a passion for data science and credit risk assessment.
- Previous internship or project experience in data analysis, data science, or related fields.
- Knowledge of financial concepts and credit risk fundamentals.
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