Huge Hiring for Data Scientist @ Banaglore in Leading MNC

Job Description

• Job Request/Description Job Overview: The Staff Data Scientist will work in teams addressing statistical machine learning and data understanding problems in a commercial technology and consultancy development environment. In this role you will contribute to the development and deployment of modern machine learning operational research semantic analysis and statistical methods for finding useful insights and recommendations for bio-process bio-pharmaceutical clinical and bio-medical industry. As a Staff Data Scientist you will be part of a data science or cross-disciplinary team on commercially-facing development projects typically involving large complex data sets. These teams typically include statisticians computer scientists software developers engineers product managers and end users working in concert with partners in GE business units. Potential application areas include remote monitoring and diagnostics across infrastructure and industrial sectors financial portfolio risk assessment and operations optimization. Essential Responsibilities: In this role you will: Work with customers to capture data and analytics requirements Develop verify and validate analytics to address customer needs and opportunities. Work alongside software developers and software engineers to translate algorithms into commercially viable products and services. Work in technical teams in development deployment and application of applied analytics predictive analytics and prescriptive analytics. Perform exploratory and targeted data analyses using descriptive statistics and other methods. Work with data engineers on data quality assessment data cleansing and data analytics Generate reports annotated code and other projects artifacts to document archive and communicate your work and outcomes. Communicate methods findings and hypotheses with stakeholders. Basic Qualifications: Masters Degree in a STEM major (Science Technology Engineering Mathematics) plus 7 years analytics development for industrial applications in a commercial/industrial setting OR Ph.D. in a STEM major (Science Technology Engineering Mathematics) plus 3 year analytics development for industrial applications in a commercial/industrial setting Solid knowledge in statistics and mathematics good understanding of machine learning and data mining algorithms Clear logic and mind in problem analyzing and team communication Demonstrated expertise in modeling and in the development and application of descriptive applied and predictive analytics on industrial challenges Proven ability in successful leading and managing data analysis projects end to end independently Demonstrated skill at data preprocessing data modeling data quality assessment Demonstrated skill in the use of one or more analytic software tools or languages (Python R) Desired Characteristics: - Please limit the desired characteristics to 12 points total (4 in each section as shown below and align it to the capabilities required for the job) Technical Expertise: Demonstrated skill in analyzing the challenges and setting up the problem-solving direction Demonstrated skill in using the right algorithms to analyze the data and provide meaningful insights Demonstrated skill in research ability for the new algorithm deployment and development Demonstrated skill in feature extraction and real-time analytics development and deployment Domain Knowledge: Demonstrated skill in understanding one or more field of bio-process bio-pharmaceutical clinical and bio-medical industry Demonstrated skill in defining and delivering customer value Leadership: Demonstrated skill in summarizing the project achievements to communicate with customer and internal team Demonstrated skill in good and efficient communication with customer and internal team Demonstrated skill at working in a team setting and leading the team with good teamwork Personal Attributes: Demonstrated awareness of how to succeed in ambiguous circumstances Please refer to the Job description above

Job Summary