About the Company
Bank of America is one of the world’s leading financial institutions, serving individual consumers, small and middle-market businesses and large corporations with a full range of banking, investing, asset management and other financial and risk management products and services. With a robust commitment to innovation and technology, we are constantly seeking to leverage cutting-edge solutions, including machine learning, to enhance our operations, improve customer experiences, and drive strategic growth.
Job Description
Join Bank of America’s innovative New Grad Program as a Machine Learning Programmer. This is an exceptional opportunity for highly motivated and talented recent graduates to launch their careers at the intersection of finance and technology. You will contribute to the design, development, and deployment of machine learning models and algorithms that solve complex business challenges, from fraud detection and risk management to personalized customer service. You’ll work alongside experienced engineers and data scientists, receiving mentorship and professional development to accelerate your growth in the dynamic field of artificial intelligence within a global financial leader.
Key Responsibilities
- Develop, implement, and optimize machine learning algorithms and models in various programming languages (e.g., Python, Java, C++).
- Collaborate with data scientists and business analysts to understand requirements and translate them into technical solutions.
- Design and implement scalable machine learning pipelines for data ingestion, model training, and deployment.
- Perform data preprocessing, feature engineering, and model evaluation to ensure robust and accurate solutions.
- Participate in code reviews, testing, and debugging to maintain high-quality code standards.
- Monitor deployed models for performance and drift, and contribute to retraining and model updates.
- Stay updated with the latest advancements in machine learning and artificial intelligence, suggesting new tools and techniques.
- Document technical specifications, model architectures, and experimental results clearly and concisely.
Required Skills
- Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, Statistics, or a related quantitative field, obtained within the last 12 months.
- Strong programming proficiency in Python, including libraries like NumPy, Pandas, Scikit-learn, TensorFlow, or PyTorch.
- Solid understanding of machine learning principles, algorithms (e.g., regression, classification, clustering, deep learning), and statistical modeling.
- Experience with data structures, algorithms, and object-oriented programming.
- Excellent problem-solving skills and analytical thinking.
- Ability to work effectively in a collaborative team environment.
- Strong communication skills, both written and verbal.
Preferred Qualifications
- Prior internship or project experience in machine learning, data science, or software development.
- Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and MLOps practices.
- Experience with big data technologies (e.g., Spark, Hadoop).
- Knowledge of database systems (SQL, NoSQL).
- Contributions to open-source projects or relevant research publications.
Perks & Benefits
- Competitive 'Top Salary' compensation package.
- Comprehensive health, dental, and vision insurance.
- 401(k) retirement plan with company match.
- Paid time off and holidays.
- Generous parental leave.
- Tuition reimbursement and continuous learning opportunities.
- On-site fitness centers and wellness programs.
- Employee assistance program.
- Opportunities for career advancement and mentorship within a global organization.
How to Apply
If you are interested in this position, please click the "Apply Now" button below. To ensure your application is properly considered, please prepare the following:
- An up-to-date Resume or CV
- A brief cover letter summarizing your experience and motivation
Applications are reviewed on a rolling basis. Only shortlisted candidates will be contacted for an interview.
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