Data Scientist I

Job Description:This role will support regulatory (LCR), GFCC/AML and GBAM LOB Strategic implementations. This individual contributor position is responsible for working with key business partners, data and technology to establish roadmaps and deliver high value information products and analytic outcomes. Primary requirement is not related to traditional programming or systems analysis skills but to the ability to create sophisticated, value-added analytic systems that support revenue generation, risk management, operational efficiency, regulatory compliance, portfolio management, and research. These systems must overcome issues of complex data (e.g., VLDB, multi-structured, big data, etc.) as well as deployment of advanced techniques (e.g., machine learning, text mining, statistical analysis, etc.) to deliver insights. Responsible for adoption of enterprise information products through clearly communicating how enterprise information products answer material banking questions leading to decisions and actions. This role possesses an advanced degree in hard science. Able to lead or work independently on complex projects and influence strategic direction. Responsibilities: . Support key regulatory model testing, implementation, ongoing performance monitoring, and MRM documentation . Use data assets to gain insights into current processes and models . Drive processing, cleansing, and verifying the integrity of data used for analysis . Research and identify the data gaps, develop and implement remediation plan and assess the model outcome impact . Lead Data Quality metrics development and monitoring, internal process design and documentation . Extend company''s data with third party sources of information when needed. Data mining, investigation and transformationExperience / Qualifications:• 5+ years of professional experience as a Data Engineer, Data Scientist or related roles• Advanced degree or equivalent experience in a quantitative discipline.• Strong STEM background• Wholesale Banking data, particularly GBS knowledge highly desired• Understanding of machine learning techniques and algorithms, such as Gradient Boosted Trees.• Strong knowledge and proficiency in Python (scikit learn, pandas, numpy etc.) SAS, SQL• Experience with data visualization tools ex Tableau, ability to tell the story about the data, including basic statistics• Experience with transaction and credit processes and systems including the distribution and use of data for analytics, modeling, and reporting• Highly motivated, proactive and a self-starter; strong sense of ownership & ability to create and execute plans without daily oversight• Critical thinker; ability to analyze problems and identify both tactical and strategic solutions• Ability to navigate the enterprise & data assets across multiple functions• Highly organized. Effectively prioritizes and balances multiple efforts in a fast-paced, regulatory driven environmentRequired Skills• Strong STEM background• Wholesale Banking data, particularly GBS knowledge highly desired• Understanding of machine learning techniques and algorithms, such as Gradient Boosted Trees.• Strong knowledge and proficiency in Python (scikit learn, pandas, numpy etc.) SAS, SQL• Experience with data visualization tools ex Tableau, ability to tell the story about the data, including basic statistics• Experience with transaction and credit processes and systems including the distribution and use of data for analytics, modeling, and reportingDesired SkillsHadoopJob Band:H5Shift: 1st shift (United States of America)Hours Per Week:40Weekly Schedule:Referral Bonus Amount:0 --> Job Description:This role will support regulatory (LCR), GFCC/AML and GBAM LOB Strategic implementations. This individual contributor position is responsible for working with key business partners, data and technology to establish roadmaps and deliver high value information products and analytic outcomes. Primary requirement is not related to traditional programming or systems analysis skills but to the ability to create sophisticated, value-added analytic systems that support revenue generation, risk management, operational efficiency, regulatory compliance, portfolio management, and research. These systems must overcome issues of complex data (e.g., VLDB, multi-structured, big data, etc.) as well as deployment of advanced techniques (e.g., machine learning, text mining, statistical analysis, etc.) to deliver insights. Responsible for adoption of enterprise information products through clearly communicating how enterprise information products answer material banking questions leading to decisions and actions. This role possesses an advanced degree in hard science. Able to lead or work independently on complex projects and influence strategic direction. Responsibilities: . Support key regulatory model testing, implementation, ongoing performance monitoring, and MRM documentation . Use data assets to gain insights into current processes and models . Drive processing, cleansing, and verifying the integrity of data used for analysis . Research and identify the data gaps, develop and implement remediation plan and assess the model outcome impact . Lead Data Quality metrics development and monitoring, internal process design and documentation . Extend company''s data with third party sources of information when needed. Data mining, investigation and transformationExperience / Qualifications:• 5+ years of professional experience as a Data Engineer, Data Scientist or related roles• Advanced degree or equivalent experience in a quantitative discipline.• Strong STEM background• Wholesale Banking data, particularly GBS knowledge highly desired• Understanding of machine learning techniques and algorithms, such as Gradient Boosted Trees.• Strong knowledge and proficiency in Python (scikit learn, pandas, numpy etc.) SAS, SQL• Experience with data visualization tools ex Tableau, ability to tell the story about the data, including basic statistics• Experience with transaction and credit processes and systems including the distribution and use of data for analytics, modeling, and reporting• Highly motivated, proactive and a self-starter; strong sense of ownership & ability to create and execute plans without daily oversight• Critical thinker; ability to analyze problems and identify both tactical and strategic solutions• Ability to navigate the enterprise & data assets across multiple functions• Highly organized. Effectively prioritizes and balances multiple efforts in a fast-paced, regulatory driven environmentRequired Skills• Strong STEM background• Wholesale Banking data, particularly GBS knowledge highly desired• Understanding of machine learning techniques and algorithms, such as Gradient Boosted Trees.• Strong knowledge and proficiency in Python (scikit learn, pandas, numpy etc.) SAS, SQL• Experience with data visualization tools ex Tableau, ability to tell the story about the data, including basic statistics• Experience with transaction and credit processes and systems including the distribution and use of data for analytics, modeling, and reportingDesired SkillsHadoopJob Band:H5Shift: 1st shift (United States of America)Hours Per Week:40Weekly Schedule:Referral Bonus Amount:0 Job Description:This role will support regulatory (LCR), GFCC/AML and GBAM LOB Strategic implementations. This individual contributor position is responsible for working with key business partners, data and technology to establish roadmaps and deliver high value information products and analytic outcomes. Primary requirement is not related to traditional programming or systems analysis skills but to the ability to create sophisticated, value-added analytic systems that support revenue generation, risk management, operational efficiency, regulatory compliance, portfolio management, and research. These systems must overcome issues of complex data (e.g., VLDB, multi-structured, big data, etc.) as well as deployment of advanced techniques (e.g., machine learning, text mining, statistical analysis, etc.) to deliver insights. Responsible for adoption of enterprise information products through clearly communicating how enterprise information products answer material banking questions leading to decisions and actions. This role possesses an advanced degree in hard science. Able to lead or work independently on complex projects and influence strategic direction. Responsibilities: . Support key regulatory model testing, implementation, ongoing performance monitoring, and MRM documentation . Use data assets to gain insights into current processes and models . Drive processing, cleansing, and verifying the integrity of data used for analysis . Research and identify the data gaps, develop and implement remediation plan and assess the model outcome impact . Lead Data Quality metrics development and monitoring, internal process design and documentation . Extend company''s data with third party sources of information when needed. Data mining, investigation and transformationExperience / Qualifications:• 5+ years of professional experience as a Data Engineer, Data Scientist or related roles• Advanced degree or equivalent experience in a quantitative discipline.• Strong STEM background• Wholesale Banking data, particularly GBS knowledge highly desired• Understanding of machine learning techniques and algorithms, such as Gradient Boosted Trees.• Strong knowledge and proficiency in Python (scikit learn, pandas, numpy etc.) SAS, SQL• Experience with data visualization tools ex Tableau, ability to tell the story about the data, including basic statistics• Experience with transaction and credit processes and systems including the distribution and use of data for analytics, modeling, and reporting• Highly motivated, proactive and a self-starter; strong sense of ownership & ability to create and execute plans without daily oversight• Critical thinker; ability to analyze problems and identify both tactical and strategic solutions• Ability to navigate the enterprise & data assets across multiple functions• Highly organized. Effectively prioritizes and balances multiple efforts in a fast-paced, regulatory driven environmentRequired Skills• Strong STEM background• Wholesale Banking data, particularly GBS knowledge highly desired• Understanding of machine learning techniques and algorithms, such as Gradient Boosted Trees.• Strong knowledge and proficiency in Python (scikit learn, pandas, numpy etc.) SAS, SQL• Experience with data visualization tools ex Tableau, ability to tell the story about the data, including basic statistics• Experience with transaction and credit processes and systems including the distribution and use of data for analytics, modeling, and reportingDesired SkillsHadoopShift:1st shift (United States of America)Hours Per Week: 40

Created: 2021-11-29