• Vice President - Data Science - Mumbai - India Jobs in Mumbai,India - 25331107

  • JPMorgan Chase & Co
  • Save Job
  • 2 - 5 Years
  • Posted : above 1 month

Job Description:

Vice President - Data Science - Mumbai - India Req # 190108948

Location Mumbai, MH, IN

Job Category Sales/Trading/Research

CIB Data Analytics Line of Business aligned Data Analytics team

Vice President, Data Scientist
The Data Analytics team at JPMorgan Corporate Investment Bank combines cutting edge machine learning techniques with the companys unique data assets to optimize all the business decisions we make In this role, 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 Our work spans the companys lines of business, with exceptional opportunities in each

The successful candidate will apply data analytics techniques from traditional statistics to data engineering and some machine learning for banking applications including risk assessment, anti-money laundering detection, trading pricing models, client data remediation and client relationship management Machine learning techniques will include familiarity or knowledge of at least one of the following areas time series analysis, supervised learning, pattern detection, natural language, maximum entropy models and neural networks

Responsibilities

Develop scalable tools leveraging machine learning and deep learning models to solve real-world problems in areas such as Speech Recognition, Natural Language Processing and Time Series predictions

Collaborate with all of JPMorgans lines of businesses and functions in the Corporate Investment Bank Markets, Global Investment Banking, Corporate Banking, Technology and Operations

Lead your own project Suggest, collect and synthesize requirements Create an effective roadmap towards the deployment of a production-level machine learning application

Qualifications

Technical

MS or PhD in a quantitative discipline, eg Computer Science, Mathematics, Statistics, Operations Research, Data Science, or similar BS with 2 years of experience in a highly quantitative position

2-5 years of hands-on experience developing statistics models and machine learning models

Strong ability to develop and debug in Python, Java, C or C Proficient in git version control R and Matlab are also relevant

Strong experience with machine learning APIs and computational packages (TensorFlow, Theano, PyTorch, Keras, Scikit-Learn, NumPy, SciPy, Pandas, statsmodels)

Experience with big-data technologies such as Hadoop, Spark, SparkML, etc

Familiarity with basic data table operations (SQL, Hive, etc)

Experience in Deep Learning DNN, CNN, RNN/LSTM, GAN or other auto encoder (AE)

Problem solving and collaboration skills Should be able to work both individually and collaboratively in teams, in order to achieve project goals

Must be curious, hardworking and detail-oriented, and motivated by complex analytical problems

Must have the ability to design or evaluate intrinsic and extrinsic metrics of your models performance which are aligned with business goals

Must be able to independently research and propose alternatives with some guidance as to problem relevance

Must be able to undertake basic and advances EDA, may require some direction from more senior team; should be aware of limitation and implication of methodology choices

Ensures re-use and sharing of ideas within team and locale

Able to work with non specialists in a partnership model, conveys information clearly and creates a sense of trust with stakeholders

Shows institutional awareness and some understanding of applied problem solving, may require coaching and guidance as to how to most rapidly reach a satisfactory conclusion

Profile Summary:

Employment Type : Full Time
Eligibility : Any Graduate
Industry : Financial Services/Stockbroking
Functional Area : IT Software : Software Products & Services
Role : Software Engineer
Salary : As per Industry Standards
Deadline : 06th Jun 2020

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