JPMorgan Chase is looking for a Data Scientist Associate Senior to lead analytical strategies and tie analytics to business results within their Consumer and Investment Banking Financial Analytics team.
Requirements
- Proficient programming skills in python and knowledge of software engineering best practices
- Strong knowledge of basic data science libraries in Python (NumPy, pandas, scikit-learn, pyspark)
- Understanding of the main deep-learning frameworks such as PyTorch, TensorFlow, Keras
- Experience with Linux and shell scripting and experience with LaTeX
- Solid understanding of traditional data science techniques and experience with data engineer pipelines for big data
- Solid knowledge of RNNs, and LSTMs models.
- Experience in big data platforms such as Databricks, AWS EMR, Sagemaker, Apache Glue, Spark, etc.
Responsibilities
- Develop and deploy machine learning models and generative AI capabilities.
- Design, code, test, and debug applications.
- Develop insights, methods, or tools using various analytic methods such as causal-model approaches, predictive modeling, regressions, machine learning, time series analysis, etc.
- Handle large amounts of data from multiple and disparate sources, employing advanced Python and SQL techniques to ensure efficiency and accuracy.
- Uphold the highest standards of data integrity and security, aligning with both internal and external regulatory requirements and compliance protocols.
- Manage project lifecycle and software development deliverables.
- Solve complex problems and handle ambiguity with strong analytical skills.
Other
- Collaborate with cross-functional teams to achieve common goals.
- Keep stakeholders informed on development progress and benefits.
- Bachelors or Masters Degree in Finance, Quantitative Finance, Data Science, Economics, or a related field.
- Experience/understanding of cloud storage (Object Stores like S3, Blob; NoSQL like Columnar, Graph databases).
