- In this team you will be responsible to develop and implement machine learning models/ statistical models/ segmentations/strategies, possibly leveraging big data and distributed computing platforms, with applications in risk management for its consumer and small business portfolio. You will help to drive long term profitable growth with strong business acumen, collaborate in a team environment, and effectively communicate results to senior management. - If you are intellectually curious and have a passion for driving solutions across organizational boundaries, you may be the perfect fit for our team. Job Responsibilities: - Utilize cutting-edge approaches to design and develop sophisticated machine learning models to drive impactful decisions for the business - Leverage big data/distributed computing/cloud computing platforms to optimize and accelerate model development processes - Work closely with the senior management team to develop ambitious, innovative modeling solutions and deliver them into production - Collaborate with various partners in marketing, risk, technology, model governance, etc. throughout the entire modeling lifecycle (development, review, deployment, and use of the models) Required qualifications, capabilities, and skills - Ph.D. or MS degree in Mathematics, Statistics, Computer Science, Operational Research, Econometrics, Physics, or other related quantitative fields - Deep understanding of advanced machine learning algorithms (e.g., regressions, XGBoost, Deep Neural Network - CNN and RNN, Clustering, Recommendation) as well as design and tuning - 5+ years of experience in developing and managing predictive risk models in financial industry - Strong ownership and execution; proven experience in implementing models - Demonstrated experience in designing, building, and deploying production quality machine learning models such as XGBoost, GBM, etc. Experience in interpreting deep learning models is a plus Preferred qualifications, capabilities, and skills: - At least one year of experience and proficiency in coding (e.g., Python, Tensorflow, Spark, or Scala) and big data technologies (e.g., Hadoop, Teradata, AWS cloud, Hive) - Demonstrated expertise in data wrangling and model building on a distributed Spark computation environment (with stability, scalability and efficiency). GPU experience is desired JPMorgan Chase & Co., one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world's most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management. We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. In accordance with applicable law, we make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as any mental health or physical disability needs. Note : For your candidature to be considered on this job, you need to apply necessarily on the company's redirected page of this job. Please make sure you apply on the redirected page as well.

Mumbai

JP Morgan Chase  - Associate - Machine Learning Risk Modeling - Fraud Analytics 

Job Description for JP Morgan Chase  - Associate - Machine Learning Risk Modeling - Fraud Analytics  in JP Morgan Chase in  Mumbai for (5-10) years of experience. Apply Now!