Machine Learning Engineer - Data Pipelines, Analyst job opportunity at MUFG (Mitsubishi UFJ Financial Group).



DateMore Than 30 Days Ago bot
MUFG (Mitsubishi UFJ Financial Group) Machine Learning Engineer - Data Pipelines, Analyst
Experience: 2-years
Pattern: full-time
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Salary:
Status:

Analyst

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degreeAssociate
loacation Jersey City, NJ, United States Of America
loacation Jersey City, N..........United States Of America

Do you want your voice heard and your actions to count? Discover your opportunity with Mitsubishi UFJ Financial Group (MUFG), one of the world’s leading financial groups. Across the globe, we’re 150,000 colleagues, striving to make a difference for every client, organization, and community we serve. We stand for our values, building long-term relationships, serving society, and fostering shared and sustainable growth for a better world. With a vision to be the world’s most trusted financial group, it’s part of our culture to put people first, listen to new and diverse ideas and collaborate toward greater innovation, speed and agility. This means investing in talent, technologies, and tools that empower you to own your career. Join MUFG, where being inspired is expected and making a meaningful impact is rewarded. The selected colleague will work at an MUFG office or client sites four days per week and work remotely one day. A member of our recruitment team will provide more details.   Job Summary The Data Management Engineering team is embarking on a transformative journey to define, enable, and drive our data strategy. We aim to engage with partners across technology, data, business, and operations to develop and deliver business outcomes. Our team is seeking a motivated and detail-oriented Entry-Level Machine Learning Engineer to join our growing team. As a key contributor, you will help build, test, and deploy machine learning models that solve real-world problems and enhance our data-driven decision-making. This is a great opportunity for someone eager to apply their academic knowledge in a practical, fast-paced environment. Major Responsibilities Assist in designing, training, and validating machine learning models using structured and unstructured data Collaborate with data scientists, analysts, and software engineers to develop production-ready ML solutions Preprocess and clean large datasets to prepare for modeling Conduct experiments, evaluate model performance, and tune hyperparameters Write reusable, well-documented code in Python (or similar languages) Contribute to model deployment pipelines and MLOps infrastructure Stay current with the latest research, tools, and trends in machine learning and AI Qualifications Bachelor’s degree in computer science, Data Science, Engineering, Mathematics, Statistics, or a related field 1 to 2 years of foundational knowledge of machine learning concepts and algorithms (e.g., regression, classification, clustering) Proficiency in Python and ML libraries such as Scikit-learn, Pandas, NumPy, TensorFlow, or PyTorch Familiarity with data manipulation, feature engineering, and exploratory data analysis Understanding of model evaluation metrics and techniques Good communication and teamwork skills Preferred Qualifications Internship or project experience involving machine learning or data science Familiarity with version control (e.g., Git), Jupyter notebooks, and cloud platforms (e.g., AWS, GCP, or Azure) Exposure to LLM and Agentic AI Exposure to SQL and basic database concepts Enthusiastic about learning and growing in the field of AI/ML Visa sponsorship/support is based on business needs. We do not anticipate providing visa sponsorship/support for this position. The typical base pay range for this role is between $82K - $121K depending on job-related knowledge, skills, experience, and location. This role may also be eligible for certain discretionary performance-based bonus and/or incentive compensation. Additionally, our Total Rewards program provides colleagues with a competitive benefits package (in accordance with the eligibility requirements and respective terms of each) that includes comprehensive health and wellness benefits, retirement plans, educational assistance and training programs, income replacement for qualified employees with disabilities, paid maternity and parental bonding leave, and paid vacation, sick days, and holidays. For more information on our Total Rewards package, please click the link below.                   MUFG Benefits Summary We will consider for employment all qualified applicants, including those with criminal histories, in a manner consistent with the requirements of applicable state and local laws (including (i) the San Francisco Fair Chance Ordinance, (ii) the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, (iii) the Los Angeles County Fair Chance Ordinance, and (iv) the California Fair Chance Act) to the extent that (a) an applicant is not subject to a statutory disqualification pursuant to Section 3(a)(39) of the Securities and Exchange Act of 1934 or Section 8a(2) or 8a(3) of the Commodity Exchange Act, and (b) they do not conflict with the background screening requirements of the Financial Industry Regulatory Authority (FINRA) and the National Futures Association (NFA). The major responsibilities listed above are the material job duties of this role for which the Company reasonably believes that criminal history may have a direct, adverse and negative relationship potentially resulting in the withdrawal of conditional offer of employment, if any. The above statements are intended to describe the general nature and level of work being performed. They are not intended to be construed as an exhaustive list of all responsibilities duties and skills required of personnel so classified. We are proud to be an Equal Opportunity Employer and committed to leveraging the diverse backgrounds, perspectives and experience of our workforce to create opportunities for our colleagues and our business. We do not discriminate on the basis of race, color, national origin, religion, gender expression, gender identity, sex, age, ancestry, marital status, protected veteran and military status, disability, medical condition, sexual orientation, genetic information, or any other status of an individual or that individual’s associates or relatives that is protected under applicable federal, state, or local law.  

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