JPMorgan Data Scientist Associate Sr - Analytics Reporting 

India, Karnataka, Bengaluru 

750479079

As a Data Scientist Associate Sr at JP Morgan Chase within the Asset and Wealth Management Technology, you will be part of our industry-leading data analytics team, and advance the state-of-the-art in financial applications ranging from generating business intelligence to predictive models and automated decision making. The role will be in the firm’s Applied AI and Machine Learning organization and will involve working closely with financial advisors, investors, client service, and operations.

Job responsibilities

• Collaborate with business stakeholders to formulate relevant financial and business questions that can be answered by data analysis.
• Research and analyze data sets using a variety of statistical and machine learning techniques.
• Communicate final results and give context.
• Document approach and techniques used.
• Work on longer term projects, building tooling that can be used to scale certain types of analyses across multiple datasets and business use cases.
• Collaborate with other J.P. Morgan machine learning teams.

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 3+ years applied experience
• Degree in a quantitative discipline, e.g. Computer Science, Mathematics, Statistics, Engineering, Data Science, or similar BS with experience in a highly quantitative position.
• Hands-on experience analyzing data.
• Strong ability to develop and debug in Python or similar professional programming language.
• Problem solving and collaboration skills.
• Should be able to work both individually and collaboratively in teams, in order to achieve project goals.
• Curious, hardworking and detail-oriented, and motivated by complex analytical problems.
• Ability to design or evaluate intrinsic and extrinsic metrics of your model’s performance which are aligned with business goals.
• Independently research and propose alternatives with some guidance as to problem relevance.
• Undertake basic and advanced EDA, may require some direction from more senior team; should be aware of limitation and implication of methodology choices.

Beneficial Skills

• Some experience with machine learning APIs and computational packages (examples: TensorFlow, PyTorch, Keras, Scikit-Learn, NumPy, SciPy, Pandas, statsmodels).
• Experience with big-data technologies such as Hadoop, Spark, SparkML, etc.
• Strong background in Mathematics and Statistics and knowledge of Financial Markets products
• Ability to develop and debug production-quality code and familiarity with continuous integration models and unit test development