Job Id: 20200909006
Job Role: Data Scientist
Experience: 10+ Years
Job Location: Bangalore
Salary: Best in Industry
Vacancies: Not Mentioned
Job Description Alstom Recruitment Bangalore Job Vacancies Hiring for Data Scientist in September 2020:
Alstom announces an opening for a Lead Data Scientist at our Bangalore, India site. This position supports the ADM Mobility Analytics program by researching, proposing, developing, testing, validating, and industrializing Machine Learning (ML) algorithms for different data-driven applications in the Mobility domain. The main goal of the ADM Mobility Analytics program is to streamline our analytics portfolio in order to improve customer performance and experience using existing and new data analytics, supported by advanced simulations and domain experts. The main purpose of this position is to develop zero-to-hero analytics applications (‘proof of concept” to “proof of value”) in maintenance, operations, energy, and city flow domains and secure successful field trials with our customers. In this capacity, you will be able to lead the R&D and deployment of our next generation data-driven solutions for the Mobility industry, within a lean startup environment, in collaboration with engineering & mobility experts, data engineers, DevOps/software engineers, and HMI designers/storytellers.
Develop approaches to mine, extract, and normalize various types of information from numerous disparate data sources, based on the customer requirements.
Develop industrial-grade analytics modules and tools designed to address business needs and solve complex problems. This includes designing, coding, validating, testing, automating, and scaling ML/data science algorithms to meet TRL8 requirements.
Suggest and apply a strong testing and quality assurance practices.
Support proof-of-concept field trials with our customers using the mobility analytics software modules and tools.
Present results in a clear manner using interactive dashboards and reports.
Attend meetings, submit work progress reports, and perform related duties as required.
Support building the data science team with recruiting process, needed tools and required trainings.
Educational Qualifications and Related Experience:
M.S. degree (with supplemented training) in data analytics, data science, machine learning, or applied mathematics. Ph.D. degree in the fields of machine learning or statistics or applied mathematics is strongly preferred.
Ten or more (10+) years of experience in two (2) or more of the following: data analytics, machine learning, AI. Theoretical knowledge would not be considered.
Strong background with time series data analytics (prediction, pattern detection, anomaly detection, trending/seasonality).
Working knowledge of predictive maintenance and PHM (preferable in the Mobility industry).
Highly proficient with python and a standard set of python libraries for machine learning and statistics.
Experience with python-based visualization libraries (such as plotly, streamlit, and dash) for developing interactive data-driven applications. Candidates will be asked to demonstrate their previous projects.
Experience with developing applications in MS Azure using open-source libraries and MS Azure DevOps.
Experience with git, github, and release management tools.
Fluent in English. French is a plus.
Experience with PowerBI, QlikView, and Grafana visualization tools.
Experience in building NLP/NLU applications using free text and log files (spaCy, BERT, GPT-2/3, Transformers, Transfer Learning)
Experience with Traffic Modeling.
Experience with LINUX environment (shell scripting)
Competences and Non-technical Skills:
Passion for developing efficient, testable, scalable, and well-documented code.
Excellent analytical, problem solving, and organizational skills.
Ability to work successfully with both local and remote / international teams.
Ability to pay close attention to detail, meet deadlines, balance multiple tasks, work well under pressure, and work with frequent interruptions.
Perspective candidates will be asked to present their previous work (if possible) in order to demonstrate their data science and machine learning proficiency levels.
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