Data Science Analyst (Financial Industry)

Job description

Lead Data Science Analyst – Financial Institution

Job description

Do you want to contribute to making today’s interconnected financial world safer utilizing your skills and experience in sophisticated data query and advanced analytics? Do you want to be part of an exciting journey where data talks to you, you make sense of data and you help management make business decisions based on Big Data?

What is your role?

As a senior data science analyst, you will lead the development and implementation of advanced analytics for analyzing data problem surrounding the credit card business, providing solutions across a range of functions, including customer segmentation, optimization, prescriptive analytics, and machine learning based decision making on Big Data. You will operate as a subject matter expert on statistical analysis of customer data and providing management with effective modeling & application for financial impact analysis, while presenting and providing insight into periodic performance metrics. You will collaborate with cross-functional partners to understand their business needs, formulate, and complete end-to-end analysis that includes data gathering and analysis. Your projects will culminate in delivering effective presentations of findings and recommendations to multiple levels of leadership, creating visual displays of quantitative information.

What will you bring?

You will bring deep skillset in database management in conducting complex data queries for data segmentation and data trend identification, data analysis skills to provide investigative and predictive solutions for management using data analytics including machine learning and interactive object-oriented programming language, such as Python. You will have fundamental business knowledge and finance exposure to understand the business surrounding loan management and credit assessment. You will have the insight and exposure to review relevant data set to identify applicable solution that may require understanding dynamic data types, classes, and software expertise to analyze and make decision on such data. You will demonstrate your ability to thrive in a fast-paced, self-learning, flexible, and empowered environment. It is essential that as a data scientist, you are skilled at problem-solving, solution conceptualization & design, logical thinking & implementation, and high-quality coding. Therefore, you will be part of a team of trailblazers led by industry veterans and will help directly build the culture, growth and success within a financial institution.

What You will Do?

· You will develop and automate reports, iteratively build prototypes & dashboards to provide insights at scale for solving for analytical needs in harnessing the power of Big Data.

· You will facilitate implementation of work product and ensure accuracy of your deliverables under the supervision of the chief data scientist.

· You will consistently follow standard work processes and documentation requirements and will recommend improvement to work processes to increase efficiency while maintaining quality.

· You will continuously improve technical and leadership skills through training and development.

· You will research, develop, and solve new emerging technology driven data problem in the financial crime industry.

What We Are Looking For?

· Bachelors/master’s degree in Analytical filed, such as Economics, Engineering, Statistics, Finance, Science, or any Quantitative based, data intensive field with Data Science exposure

· 3+ years of experience in Credit risk, Fraud risk, Optimization, Operations Analytics, Modeling/Data Science

· 1 to 2+ years of professional experience in Machine Learning and Artificial Intelligence in project development capacity, whether masters’ thesis/project or corporate project

· Deep knowledge of data, in understanding the capability of Big Data, pitfalls of Big Data

· Extensive and proficient SQL expertise is mandatory, while Python Coding is preferred with a solid understanding of OOPS concepts

· Experience with all phases of the software development cycle, including design, implementation, and operation of production systems

· Good understanding of fundamental python packages & environments, such as Numpy, Pandas, matplotlib, SciPy, caffe, etc.

Job Type: Full-time

Salary: Up to $125,000.00 per year

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