Company Name:-
Philips

Job Location:-
Bengaluru, Karnataka

Job Summary:-
Job Title
Specialist II – Data Science
Job Description
In this role, you have the opportunity to
Business deliverables which includes Machine Learning based model development and data analysis activities of Digital Twin proposition
You are responsible for
Work with service innovation leaders and R&D leaders to identify opportunities for leveraging system log data to drive serviceability solutions
Designs the architecture and the analytics pipelines while taking into account appropriate time frames, and costs.

Mine and analyze data from system log central database to drive system diagnostics efficiency
Develop custom data models and algorithms to apply to data sets
Define strategy to develop predictive modelling to increase system reliability
Selecting features, building and optimizing classifiers using machine learning and deep learning techniques
Collaborates with Data Engineers to enhance data collection and ingestion/curation techniques to include information that is relevant for building analytic systems
Processing, cleansing, and verifying the integrity of data used for analysis
Contribute the technical road mapping for the team
Coordinate with different functional teams to implement models, processes, monitoring of data accuracy & outcomes
To succeed in this role, you should have the following skills and experience
Master’s degree in Computer Science, Information management, Statistics or related field, with 6 to 8 years of experience in the Healthcare industry manipulating data sets and building predictive models with focus on product development
Experience in statistical modelling, machine learning, data mining, unstructured data analytics and natural language processing.

Sound understanding of – Bayesian Modelling, Classification Models, Cluster Analysis, Neural Network, Nonparametric Methods, Multivariate Statistics, etc.

Strong hands on knowledge of ML techniques like regression algorithms, K-NN, Naïve Bayes, SVM and ensemble techniques like Random forest, AdaBoost etc
Having strong knowledge in unsupervised learning algorithms using Neural networks and Deep-Learning
Strong knowledge in Data Wrangling and Exploration techniques to identify the patterns, trends and outliners.

Deep knowledge and practi

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