BSA Data Scientist

East West Bank•New York, NY

22h•$70,000 - $120,000

About The Position

Data Scientist works closely with business partners to turn data into critical information and knowledge that can be used to make sound anti-money laundering (AML), sanctions, and fraud risk management decisions. The individual must be detail oriented, able to manage multiple tasks, and lead data-driven changes. Collects large amounts of data using analytical, statistical, and programmable skills. It is their responsibility to use data to develop solutions tailored to meet the organization’s unique needs.

Requirements

Programming Skills – knowledge of statistical programming languages like R, Python, and database query languages like SQL, Hive, Pig is desirable.
Statistics – Good applied statistical skills, including knowledge of statistical tests, behavior clustering, distributions, regression, maximum likelihood estimators, etc. Proficiency in statistics is essential for data-driven companies.
Strong Math Skills (Multivariable Calculus and Linear Algebra) - understanding the fundamentals of Multivariable Calculus and Linear Algebra is important as they form the basis of a lot of predictive performance or algorithm optimization techniques.
Data Wrangling – proficiency in handling imperfections in data is an important aspect of a data scientist job description.
Experience with Data Visualization Tools like Tableau and Power BI that help to visually encode data
Network/Link Analytics
Excellent Communication Skills – it is incredibly important to describe findings to a technical and non-technical audience.
Strong Software Engineering Background
Hands-on experience with data science tools
Problem-solving aptitude
Analytical mind and great business sense
Applicants must have legal authorization to work in the United States.
We do not offer visa sponsorship at this time.

Nice To Haves

Familiarity with Scala, Java, or C++ is an added advantage.

Responsibilities

Data mining or extracting usable data from valuable data sources
Using machine learning tools to select features, create and optimize classifiers
Carrying out the preprocessing of structured and unstructured data
Enhancing data collection procedures to include all relevant information for developing analytic systems
Processing, cleansing, and validating the integrity of data to be used for analysis
Analyzing large amounts of information to find patterns and solutions
Developing prediction systems and machine learning algorithms
Presenting results in a clear manner
Propose solutions and strategies to tackle business challenges
Collaborate with Business and IT teams

Benefits

Sustained growth and expertise in industries like real estate, entertainment and media, private equity and venture capital, and high-tech help build sustainable businesses and expand our associates’ potential for career advancement.

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