Banking + 2 more
Description
Qualifications and Experience
Degree in Statistics, Machine Learning, Mathematics, Computer Science, Economics, or any other related quantitative field.
Working experience in the finance industry via direct employment or consultancy is preferred
1-3 years’ experience in working with structured and unstructured data (e.g. Streams, images) Understanding of data flows, data architecture, ETL and processing of structured and unstructured data. Using data mining to discover new patterns from large datasets. Implement standard and proprietary algorithms for handling and processing data. Experience with common data science toolkits. Experience with data visualization tools, such as Power BI, Tableau, etc.
Proficiency in application and web development. Structured and Unstructured Query languages e.g. SQL, Power BI; QlikView; Tableau, R, Python, JSON, Java, HTML
Experience with the use of GIT
Responsibilities
Support in the gathering of data for use in Data Science models, ensuring that chosen datasets best reflect the organization's goals.
Perform data pre-processing including data manipulation, transformation, normalization, standardization, visualization, and derivation of new variables/features.
Document business requirements
Develop model documentation for the purpose of model validation
Develop dashboards and presentations for business insights using tools like Power BI and Microsoft power point
Utilize advanced data analytics and mining techniques to analyze data, assess data validity and usability; reviews data results to ensure accuracy; and communicate results and insights to stakeholders.
Use data profiling and visualization techniques using tools to understand and explain data characteristics that will inform modelling approaches.
Communicate data information to business with various skill levels and in various roles, presenting trends, correlations and patterns found in complicated datasets in a manner that clearly and concisely conveys meaningful insights and defend recommendations.
Develops and maintains optimal evaluation techniques to ensure that modelled outcomes are rigorous and creates model performance tracking.
Competent in Machine Learning programming in Python, with supplementary still in Java, etc. Familiar with the Hadoop distributed computational platform, including broader ecosystem of tools such as HDFS / Spark / Kafka
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