Intern Data Scientist
hace 3 semanas
The Spec Analytics Analyst is a trainee professional role. Requires a good knowledge of the range of processes, procedures and systems to be used in carrying out assigned tasks and a basic understanding of the underlying concepts and principles upon which the job is based. Good understanding of how the team interacts with others in accomplishing the objectives of the area. Makes evaluative judgements based on the analysis of factual information. They are expected to resolve problems by identifying and selecting solutions through the application of acquired technical experience and will be guided by precedents. Must be able to exchange information in a concise way as well as be sensitive to audience diversity. Limited but direct impact on the business through the quality of the tasks/services provided. Impact of the job holder is restricted to own job.
Responsibilities:
Qualifications:
Education:
This job description provides a high-level review of the types of work performed. Other job-related duties may be assigned as required.
As a Data Science Intern, you will apply a variety of statistical techniques to measure high-impact strategies, promoting consumer growth, financial inclusion, and incremental revenue across Consumer Banking products. You will work with cross-functional teams (Pricing, Modelling, Risk, Product Management, Behavioral Economics, and more) and experienced professionals to learn from real-world industry problems. Our collaborative, proactive environment encourages creativity and values your insights, and will provide you with training and mentorship from leaders in the finance and data science industry. The role provides the possibility to transition into a full-time role upon graduation.
Key Responsibilities/Learning Opportunities:
Work with large and complex datasets to develop comprehensive analysis from various data sources and categories (demographic, financial, credit bureau, transactional data, social media, digital, etc.) to understand relationships, patterns, and trends from data. Develop statistical valuation and tracking methodologies for key initiatives to better understand consumer-product dynamics and contribute to the overall strategic decision-making. Lever AI to improve the decision framework on critical decision across the bank Participate in the development, automation, monitoring and improvement of predictive models and machine learning algorithms.Requirements, skills and competencies:
Strong problem-solving and analytical skills and eagerness to learn new technologies and methods. Currently enrolled as a final year student or recent graduates in actuarial science, mathematics, engineering, computer science, economics, or related quantitative field. 1+ years of academic/work experience in statistics, computer science and/or financial analysis. Basic programming and statistical analysis skills (experience with Python, Spark Tableau, SQL). Technical knowledge in testing, sampling, predictive modelling, machine learning, object-oriented Programming is preferred but not mandatory. Leadership and interpersonal skills to generate synergies with cross-functional teams. Self-organized, collaborative, proactive and creative. Excellent verbal and written communication skills in both English and Spanish (English Intermediate Level).------------------------------------------------------
Job Family Group:
Decision Management------------------------------------------------------
Job Family:
Specialized Analytics (Data Science/Computational Statistics)------------------------------------------------------
Time Type:
Full time------------------------------------------------------
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