Company Name:-
Ericsson

Job Location:-
Bengaluru, Karnataka

Job Summary:-
As the tech firm that created the mobile world, and with more than 54,000 patents to our name, we’ve made it our business to make a mark.

When joining our team at Ericsson you are empowered to learn, lead and perform at your best, shaping the future of technology.

This is a place where you’re welcomed as your own perfectly unique self, and celebrated for the skills, talent, and perspective you bring to the team.

Are you in?
Come, and be where it begins.

Our Exciting Opportunity
Responsible for developing scientific methods, processes, and systems to extract knowledge or insights to drive the future of applied analytics.

Provide thought leadership, perform Advanced Statistical Analytics, and create insights into data to provide to the business actionable insights, identify trends, and measure performance which address business problems.

Collaborate with business and process owners to understand business issues, and with engineers to implement and deploy scalable solutions, where applicable.

You will:
Perform Data science leadership
Synthesize problems into data question(s)
Decide approach for data science
Design & perform data science experiment
Develop Data Science Infrastructure &Tools
Convert data into actionable insights.

Act in external relations
To be successful in the role you must have:
Theoretical Knowledge:
Common and advanced Clustering algorithms including probability density and distribution based.

Convolutional Neural networks
Recurrent Neural Networks
Bayesian based probabilistic graphical models
Deep Autoencoders
Latest machine reasoning techniques
Reinforcement learning
Application of ML/AI:
Clean clustering of high dimensional data with noise
Application of autoencoders to high-dimensional data
Application of CNN to high-dimensional temporal data
Application of RNN to high- time series data for forecasting
Application of Bayesian dimensional networks for causal reasoning
Auto learning of network structure from data for probabilistic graphical models
Frameworks, Languages, & General skills:
Strong programming skills in Python, ability to write object oriented and scalable code
JupyterHub and notebooks
Strong skills in the use of current state of the art machine learning frameworks such as Tensor

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