Data Scientist I or II

Key Skills

Java Programming, JQuery, Python Programming, SQL, Apache Hadoop, NoSQL, Apache Hive, Apache Pig, SPARK Programming

Job Description

We are seeking a motivated candidate who is experienced in solving complex problems and displays a passion for stopping bad actors and protecting our

customers. In this role you will utilize multiple data sources and analytical tools to develop and implement effective fraud risk management strategies to mitigate fraud loss while ensuring an appropriate balance between risk tolerance and customer experience. You must be familiar with data analysis techniques, software, and processes, and you should possess the creative problem-solving abilities necessary to suggest new methods of analysis and prevention. This job will support real-time fraud detection rule systems for a variety of monetary and non-monetary transactions (credit/debit card, check, deposits, digital payments, new account originations, identity theft, account take over, etc)

ESSENTIAL DUTIES AND RESPONSIBILITIES

Following is a summary of the essential functions for this job. Other duties may be performed, both major and minor, which are not mentioned below. Specific activities may change from time to time.

• Independently identify fraud patterns and trends utilizing advanced analytical techniques, data mining and visualization dashboards.
• Develop, validate, and implement fraud rule logic to mitigate financial loss and improve the client experience.
• Make decisions in a timely manner while balancing the need for action with the need for data analysis.
• Develop key fraud metric reporting and ongoing monitoring routines.
• Communicate fraud related incidents to key stakeholders.
• Participate in the development of business cases to support fraud strategic initiatives
• Support the company’s commitment to risk management and protecting the integrity and confidentiality of systems and data.

QUALIFICATIONS

Required Qualifications:

The requirements listed below are representative of the knowledge, skill and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

• Bachelor’s degree and zero to four or more years of experience in a quantitative field such as Finance, Mathematics, Analytics, Data Science, Computer Science, or Engineering, or equivalent education and related training
• Exhibit understanding of statistical methods, including a broad understanding of classical statistics, probability theory, econometrics, time-series, and primary statistical tests
• Familiarity with linear algebra concepts for optimization, complex matrix operations, eigenvalue decompositions, and principal components; working knowledge of calculus/differential equations, with understanding of stochastic processes
• Demonstrate understanding of data cleansing and preparation methodologies, including regex, filtering, indexing, interpolation, and outlier treatment
• Strong familiarity with data extraction in a variety of environments (SQL, JQuery, etc.)
• Working knowledge of Hadoop, Pig, Hive, and/or NoSQL, Spark
• Experience in managing multiple projects with tight deadlines in a collaborative environment

LEVEL 1:

QUALIFICATIONS

Required Qualifications:

The requirements listed below are representative of the knowledge, skill and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

• Bachelor’s degree and zero to four or more years of experience in a quantitative field such as Finance, Mathematics, Analytics, Data Science, Computer Science, or Engineering, or equivalent education and related training
• Exhibit understanding of statistical methods, including a broad understanding of classical statistics, probability theory, econometrics, time-series, and primary statistical tests
• Familiarity with linear algebra concepts for optimization, complex matrix operations, eigenvalue decompositions, and principal components; working knowledge of calculus/differential equations, with understanding of stochastic processes
• Demonstrate understanding of data cleansing and preparation methodologies, including regex, filtering, indexing, interpolation, and outlier treatment
• Strong familiarity with data extraction in a variety of environments (SQL, JQuery, etc.)
• Working knowledge of Hadoop, Pig, Hive, and/or NoSQL, Spark
• Experience in managing multiple projects with tight deadlines in a collaborative environment

Preferred Qualifications:

• Master’s degree or PhD in a quantitative field such as Finance, Mathematics, Analytics, Data Science, Computer Science, or Engineering
• Four years of relevant work experience if candidate lacks graduate degree
• Previous experience in the banking or fin-tech industry

LEVEL 2:

QUALIFICATIONS

Required Qualifications:

• The requirements listed below are representative of the knowledge, skill and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
• Bachelor’s degree and four or more years of experience in a quantitative field such as Finance, Mathematics, Analytics, Data Science, Computer Science, or Engineering, or equivalent education and related training
• Exhibit understanding of statistical methods, including a broad understanding of classical statistics, probability theory, econometrics, time-series, and primary statistical tests
• Familiarity with linear algebra concepts for optimization, complex matrix operations, eigenvalue decompositions, and principal components; working knowledge of calculus/differential equations, with understanding of stochastic processes
• Demonstrate understanding of data cleansing and preparation methodologies, including regex, filtering, indexing, interpolation, and outlier treatment
• Strong familiarity with data extraction in a variety of environments (SQL, JQuery, etc.)
• Working knowledge of Hadoop, Pig, Hive, and/or NoSQL, Spark
• Experience in managing multiple projects with tight deadlines in a collaborative environment

Preferred Qualifications:

• Master’s degree or PhD in a quantitative field such as Finance, Mathematics, Analytics, Data Science, Computer Science, or Engineering
• Four years of relevant work experience if candidate lacks graduate degree
• Previous experience in the banking or fin-tech industry