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Data Scientist IBank of America • United States
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Data Scientist I

Bank of America
  • US
    United States
  • US
    United States
Postuler Maintenant

À propos

Job Title
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, and presenting recommendations based on the findings. Job expectations include demonstrating flexibility, resilience, accountability, a disciplined approach, and a commitment to fostering responsible growth for the enterprise. Responsibilities: Performs business analytics, which include data analysis, trend identification, and pattern recognition, using advanced techniques (e.g., machine learning, text mining, statistical analysis, etc.) to support decision-making and drive data-driven insights Applies agile practices for project management, solution development, deployment, and maintenance Creates and maintains technical documentation, capturing the business requirements and specifications related to the developed analytical solution and its implementation in production Manages multiple priorities and maintains quality and timeliness of work deliverables such as quantitative models, data science products, data analysis reports, or data visualizations, while exhibiting the ability to work independently and in a team environment Delivers engaging presentations and engages in both in-person and virtual conversations that effectively communicate technical concepts and analysis results to a diverse set of internal stakeholders, and develops professional relationships to foster collaboration on work deliverables Mitigates risk by identifying potential issues and developing controls Researching the latest advances in the fields of data science and artificial intelligence to support business analytics Required Qualifications: Strong foundation in machine learning techniques, including supervised, unsupervised, and reinforcement learning, with the ability to apply these methods to complex business problems. Solid understanding of modern AI advancements, including Transformers, Large Language Models (LLMs), Generative AI, and Retrieval‑Augmented Generation (RAG) architectures. 2 -5 years of proficiency in Python and/or Java, with experience building scalable, production‑quality code. Hands‑on experience using version control systems (e.g., Git) to collaborate effectively in team‑based development environments. Demonstrated ability to analyze and decompose complex requirements, translating business needs into data‑driven and ML‑based solutions. Working knowledge of deploying and optimizing AI/ML applications on CPU and GPU infrastructures, including technologies such as CUDA, vLLM, Triton, or equivalent inference frameworks. Strong communication and interpersonal skills, with the ability to clearly explain technical concepts to both technical and non‑technical stakeholders in a regulated enterprise environment. Familiarity with cloud platforms (Azure and/or AWS) and modern MLOps or cloud‑based deployment practices. Desired / Preferred Qualifications: Advanced academic or research background in mathematics, statistics, or applied machine learning. Experience developing or maintaining Java‑based enterprise applications. Experience designing and building RESTful web services or APIs for ML or AI solutions. Exposure to NoSQL databases such as Cassandra or equivalent distributed data stores. Experience with open‑source search and indexing platforms, including Elasticsearch or SOLR. Prior experience working in Agile or Scrum development environments. Hands‑on experience building chatbots, conversational AI solutions, or internal AI productivity tools. Practical experience with Azure and/or AWS services, including compute, storage, and ML/AI tooling. Familiarity with CPU/GPU inference engines, performance optimization, or large‑scale model serving in production environments. Skills: Adaptability Attention to Detail Business Analytics Technical Documentation Written Communications Agile Practices Application Development Collaboration Data Visualization DevOps Practices Artificial Intelligence/Machine Learning Networking Policies, Procedures, and Guidelines Management Presentation Skills Risk Management Minimum Education Requirement: Minimum of Bachelor's degree in Computer Science, Data Science, Mathematics, or related field Shift: 1st shift (United States of America) Hours Per Week: 40
  • United States

Compétences linguistiques

  • English
Avis aux utilisateurs

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