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Job Description:
This job is responsible for analyzing and interpreting large datasets to uncover potential revenue generation opportunities and develop effective risk management strategies. Key responsibilities include collaborating with key stakeholders to comprehend business problems, utilizing data gathering and analysis techniques to devise solutions, delivery tasks associated with the integration, cleaning, transformation, and control of data in operational and analytical data systems and presenting recommendations based on the findings. Job expectations include providing technical thought leadership by implementing complex data solutions and interactions across multiple systems and domains.
Responsibilities:
Maintains, improves, cleans, and manipulates large data for operational and analytics data systems, builds complex processes supporting data transformation, data structures, metadata, and data quality controls
Skills:
Global Risk Analytics (GRA) and Enterprise Independent Testing (EIT) are sub-lines of business within Global Risk Management (GRM). Collectively, they are responsible for developing a consistent and coherent set of models, analytical tools, and tests for effective risk and capital measurement, management and reporting across Bank of America. GRA and EIT partner with the Lines of Business and Enterprise functions to ensure the capabilities it builds address both internal and regulatory requirements, and are responsive to the changing nature of portfolios, economic conditions, and emerging risks. In executing its activities, GRA and EIT drive innovation, process improvement and automation.
We are looking for a Data Scientist who will help us discover the information advantage hidden in vast amounts of data, and help us make smarter decisions to deliver better products and services. Your primary focus will be in applying data engineering and data science techniques, that may include machine learning, deep learning, natural language processing, statistical analysis, and building high quality prediction systems integrating with our products and services. This role will work with other data scientists in the team on data science projects to enhance revenue and mitigate risk.
Key Responsibilities:
Assembles large, complex data sets that meet requirements
Performs tasks of data wrangling and feature engineering
Performs ad-hoc analysis and presents results in a clear manner
Ensures data integrity for analysis and modeling
Data visualization
Good applied statistics skills, such as distributions, statistical testing, regression, etc.
Data-oriented approach
Ability to manage multiple and competing priorities
Excellent written and verbal communication skills
Builds and optimizes classifiers using machine learning techniques
Required Skills:
Bachelor or Advanced Degree in a STEM discipline like computer science, Engineering, Statistics, Mathematics, Bioinformatics etc.
Strong STEM background
Knowledge of Machine Learning, NLP, Statistical Modeling, Quantitative Analysis, Forecasting, Data Visualization
Knowledge of machine learning techniques and algorithms, such as Gradient Boosted Trees, CNN, RNN LSTM, etc.
Proficiency in languages such as SQL, Python (scikit learn, pandas, numpy etc.), SAS
Prior experience with SQL and NoSQL databases, distributed computing Knowledge of data visualization tools like Tableau
Minimum of 2 years of relevant experience
1st shift (United States of America)These jobs might be a good fit