Data Scientist
10 or more years of experience in data science
Ability to work effectively in a dynamic group that has several concurrent projects
Statistical analysis: Identify patterns in data. This includes having a keen sense of pattern detection and anomaly detection.
Machine learning/Artificial Intelligence: Implement algorithms and statistical models to automate data analysis, data profiling and data validation.
Develop programs and analyze large datasets to uncover answers to complex problems. Should be comfortable writing code and working in a variety of programming languages, such as Java, Python, and SQL
Serve as lead data strategist to identify and integrate new datasets that can be leveraged through our product capabilities, and work closely with the engineering team in the development of data products
Execute analytical experiments to help solve problems across banking/financial domains
Identify relevant data sources and sets to profile for client business needs, and collect large structured and unstructured datasets and variables
Devise and utilize algorithms and models to mine big-data stores; perform data profiling and analysis for continuous optimization of data; perform data quality check and validate data for uniformity and accuracy
Analyze data for trends and patterns, and interpret data with clear objectives in mind
Data storytelling/visualization: Communicate actionable insights using data, often for a nontechnical audience.
Serve as lead data strategist to identify and integrate new datasets that can be leveraged through our product capabilities, and work closely with the engineering team in the development of data products
Execute analytical experiments to help solve problems across banking/financial domains
Identify relevant data sources and sets to profile for client business needs, and collect large structured and unstructured datasets and variables
Devise and utilize algorithms and models to mine big-data stores; perform data profiling and analysis for continuous optimization of data; perform data quality check and validate data for uniformity and accuracy
Analyze data for trends and patterns, and interpret data with clear objectives in mind
skills
Data Validation
SQL
Data Analysis
Data Profiling
Experience preferably in one or many of these Transaction Monitoring (AML, Fraud), Sanctions Screening (OFAC, CDD) KYC, Trade Surveillance, Financial Crimes Risk Assessment.
10 or more years of experience in data science
Ability to work effectively in a dynamic group that has several concurrent projects
Statistical analysis: Identify patterns in data. This includes having a keen sense of pattern detection and anomaly detection.
Machine learning/Artificial Intelligence: Implement algorithms and statistical models to automate data analysis, data profiling and data validation.
Develop programs and analyze large datasets to uncover answers to complex problems. Should be comfortable writing code and working in a variety of programming languages, such as Java, Python, and SQL
Serve as lead data strategist to identify and integrate new datasets that can be leveraged through our product capabilities, and work closely with the engineering team in the development of data products
Execute analytical experiments to help solve problems across banking/financial domains
Identify relevant data sources and sets to profile for client business needs, and collect large structured and unstructured datasets and variables
Devise and utilize algorithms and models to mine big-data stores; perform data profiling and analysis for continuous optimization of data; perform data quality check and validate data for uniformity and accuracy
Analyze data for trends and patterns, and interpret data with clear objectives in mind
Data storytelling/visualization: Communicate actionable insights using data, often for a nontechnical audience.
Serve as lead data strategist to identify and integrate new datasets that can be leveraged through our product capabilities, and work closely with the engineering team in the development of data products
Execute analytical experiments to help solve problems across banking/financial domains
Identify relevant data sources and sets to profile for client business needs, and collect large structured and unstructured datasets and variables
Devise and utilize algorithms and models to mine big-data stores; perform data profiling and analysis for continuous optimization of data; perform data quality check and validate data for uniformity and accuracy
Analyze data for trends and patterns, and interpret data with clear objectives in mind
skills
Data Validation
SQL
Data Analysis
Data Profiling
Experience preferably in one or many of these Transaction Monitoring (AML, Fraud), Sanctions Screening (OFAC, CDD) KYC, Trade Surveillance, Financial Crimes Risk Assessment.