Department : The data management group works within the Risk office. The risk office is in charge of risk management across different business units. Risk office provides an independent quantitative assessment of the different carried risks of the business. The team also engage with management and commercial teams to ensure that there is a full and accurate awareness of risk and that these risks are professionally analysed and managed.&nbsp; While developing risk models, the risk team has developed an excellent understanding of different business verticals of the group. Also, the risk team has built a robust data infrastructure through sourcing data from different sources and business units. Using the robust data infrastructure sophisticated risk and machine learning models have been developed, which help different business units to take a critical business decision. The board after observing the success of Risk office infrastructure, has given risk team responsibility of data management group to build a robust data infrastructure to create a unified view of all the data, which lies scattered across different teams and use different technologies.&nbsp; The group is in charge of creating a knowledge house for internal data sources, business related data, and alternative data sources, i.e. customized data encyclopaedia for the different business units. The natural next steps to harness the capabilities of data encyclopaedia to derive actionable insights for the business units. A data scientists will help build the infrastructure and develop production ready sophisticated Machine Learning (ML)/Artificial Intelligence (AI) models. With a long track record of being able to get complicated things done, the risk team is now looking to hire exceptional data scientist for the risk office to increase its firing power. You will work directly with the Chief Risk Officer at extending our risk and analytic capabilities, written entirely in F#. Knowledge, Skills and Abilities : - A graduate degree in quantitative discipline like, computer science, mathematics, physics, and similar disciplines - An industry experience, which demonstrates building business relevant data science solutions - Excellent knowledge of data cleaning and Extract Transform Load (ETL) pipeline for the model development - Comfortable interacting with different kinds of databases and extract relevant data from the different databases - Experience with building production ready models and maintaining models in production - Strong skills in undergraduate level statistics, linear algebra, modelling fundamentals, and probability - Strong skills in computational thinking (Numerical Analysis) i.e. translating math into units of codes using appropriate data structures with optimal time complexity - Proficient in Python or R data science stack - Understanding of parallel computing and parallelizing computations using frameworks like Dask, Spark, MPI - Familiarity with Deep learning and Deep learning libraries like Keras, tensorflow, CNTK, Theano, PyTorch, Caffe - Knowledge of Natural Language Processing (NLP) fundamentals and familiarity with Python or R NLP stack - Knowledge of Machine Vision - Understanding of Bayesian Modelling, Monte-Carlo Methods and tools like Stan, PyMC3 - Good knowledge of fundamentals of time-series modelling and Time Series stack in R or Python Significant Plus : - Knowledge of functional programming paradigm or have worked on functional languages like Scala - Understanding of functional programming using F# (Fsharp) - Prior experience working in the financial industry - Experience in building econometric models - Knowledge of code versioning tools - Ability to work in a fast paced high pressure environment - Detail oriented and efficient problem solver. Ability to synthesize diverse set of information to prototype business solutions. - Should have an excellent verbal and written communication skills Key Responsibilities : The data scientist will take complete responsibility of scoping out the problem and building ML or AI models. - In the process the data scientist must collaborate with different business units, data engineers, and full-stack developers to understand the task requirements, prototype the best feasible solution, and execute the entire model development. - It is imperative that candidate is open to experiment and learn new technologies as per the task requirement.&nbsp; - The ideal candidate should be comfortable collaborating with multi-disciplinary teams and open to take leadership when required and follow directions when necessary.

Mumbai

Manager/AVP - Data Science - Manufacturing 

Manager/AVP - Data Science - Manufacturing  ,Job Description for Manager/AVP - Data Science - Manufacturing  in Michael Page in  Mumbai for (10-15) years of experience. Apply Now!

Job Description for Manager/AVP - Data Science - Manufacturing  in Michael Page in  Mumbai for (10-15) years of experience. Apply Now!