Sr Data Scientist [India]

at Egnyte

Sr Data Scientist [India]

Egnyte

Company

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Sr Data Scientist [India]

at Egnyte

Posted by Prasanth Mulleti

4 - 10 yrs

Best in industry

Remote, Mumbai

Skills

Data Science

data scientist

Machine Learning (ML)

Time series

QoS

Clustering

Forecasting

Statistical Modeling

Data mining

Decision trees

TensorFlow

PyTorch

Job Description

We are looking for an experienced engineer to join our data science team, who will help us design, develop, and deploy machine learning models in production. You will develop robust models, prepare their deployment into production in a controlled manner, while providing appropriate means to monitor their performance and stability after deployment.

What You’ll Do will include (But not limited to):

Preparing datasets needed to train and validate our machine learning models
Anticipate and build solutions for problems that interrupt availability, performance, and stability in our systems, services, and products at scale.
Defining and implementing metrics to evaluate the performance of the models, both for computing performance (such as CPU & memory usage) and for ML performance (such as precision, recall, and F1)
Supporting the deployment of machine learning models on our infrastructure, including containerization, instrumentation, and versioning
Supporting the whole lifecycle of our machine learning models, including gathering data for retraining, A/B testing, and redeployments
Developing, testing, and evaluating tools for machine learning models deployment, monitoring, retraining.
Working closely within a distributed team to analyze and apply innovative solutions over billions of documents
Supporting solutions ranging from rule-bases, classical ML techniques to the latest deep learning systems.
Partnering with cross-functional team members to bring large scale data engineering solutions to production
Communicating your approach and results to a wider audience through presentations

Your Qualifications:

Demonstrated success with machine learning in a SaaS or Cloud environment, with hands–on knowledge of model creation and deployments in production at scale
Good knowledge of traditional machine learning methods and neural networks
Experience with practical machine learning modeling, especially on time-series forecasting, analysis, and causal inference.
Experience with data mining algorithms and statistical modeling techniques for anomaly detection in time series such as clustering, classification, ARIMA, and decision trees is preferred.
Ability to implement data import, cleansing and transformation functions at scale
Fluency in Docker, Kubernetes
Working knowledge of relational and dimensional data models with appropriate visualization techniques such as PCA.
Solid English skills to effectively communicate with other team members

Due to the nature of the role, it would be nice if you have also:

Experience with large datasets and distributed computing, especially with the Google Cloud Platform
Fluency in at least one deep learning framework: PyTorch, TensorFlow / Keras
Experience with No–SQL and Graph databases
Experience working in a Colab, Jupyter, or Python notebook environment
Some experience with monitoring, analysis, and alerting tools like New Relic, Prometheus, and the ELK stack
Knowledge of Java, Scala or Go-Lang programming languages
Familiarity with KubeFlow
Experience with transformers, for example the Hugging Face libraries
Experience with OpenCV

About Egnyte

In a content critical age, Egnyte fuels business growth by enabling content-rich business processes, while also providing organizations with visibility and control over their content assets. Egnyte’s cloud-native content services platform leverages the industry’s leading content intelligence engine to deliver a simple, secure, and vendor-neutral foundation for managing enterprise content across business applications and storage repositories. More than 16,000 customers trust Egnyte to enhance employee productivity, automate data management, and reduce file-sharing cost and complexity. Investors include Google Ventures, Kleiner Perkins, Caufield & Byers, and Goldman Sachs. For more information, visit www.egnyte.com

#LI-Remote

Job Description

What You’ll Do will include (But not limited to):

Preparing datasets needed to train and validate our machine learning models
Anticipate and build solutions for problems that interrupt availability, performance, and stability in our systems, services, and products at scale.
Defining and implementing metrics to evaluate the performance of the models, both for computing performance (such as CPU & memory usage) and for ML performance (such as precision, recall, and F1)
Supporting the deployment of machine learning models on our infrastructure, including containerization, instrumentation, and versioning
Supporting the whole lifecycle of our machine learning models, including gathering data for retraining, A/B testing, and redeployments
Developing, testing, and evaluating tools for machine learning models deployment, monitoring, retraining.
Working closely within a distributed team to analyze and apply innovative solutions over billions of documents
Supporting solutions ranging from rule-bases, classical ML techniques to the latest deep learning systems.
Partnering with cross-functional team members to bring large scale data engineering solutions to production
Communicating your approach and results to a wider audience through presentations

Your Qualifications:

Demonstrated success with machine learning in a SaaS or Cloud environment, with hands–on knowledge of model creation and deployments in production at scale
Good knowledge of traditional machine learning methods and neural networks
Experience with practical machine learning modeling, especially on time-series forecasting, analysis, and causal inference.
Experience with data mining algorithms and statistical modeling techniques for anomaly detection in time series such as clustering, classification, ARIMA, and decision trees is preferred.
Ability to implement data import, cleansing and transformation functions at scale
Fluency in Docker, Kubernetes
Working knowledge of relational and dimensional data models with appropriate visualization techniques such as PCA.
Solid English skills to effectively communicate with other team members

Due to the nature of the role, it would be nice if you have also:

Experience with large datasets and distributed computing, especially with the Google Cloud Platform
Fluency in at least one deep learning framework: PyTorch, TensorFlow / Keras
Experience with No–SQL and Graph databases
Experience working in a Colab, Jupyter, or Python notebook environment
Some experience with monitoring, analysis, and alerting tools like New Relic, Prometheus, and the ELK stack
Knowledge of Java, Scala or Go-Lang programming languages
Familiarity with KubeFlow
Experience with transformers, for example the Hugging Face libraries
Experience with OpenCV

About Egnyte

#LI-Remote

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About Egnyte

Founded :

2008

Type :

Product

Size :

500-1000

Stage :

Profitable

About

Egnyte provides secure Enterprise File Sharing and Content Governance built from the Cloud down. Access, Share and Control 100% of your data from anywhere using any smartphone, tablet or computer.

Egnyte store billion of files and petabytes of data and we are looking for help to take the platform used by millions of users to the next level of scale. Autonomy and ownership is integral to our culture and engineers own one or more services end to end.

We’re looking for Engineers and they should be able to take a complex problem and work with product managers, devops and other team members to execute end to end.

Egnyte provides secure Enterprise File Sharing and Content Governance built from the Cloud down. Access, Share and Control 100% of your data from anywhere using any smartphone, tablet or computer.

We’re looking for Engineers and they should be able to take a complex problem and work with product managers, devops and other team members to execute end to end.

Prasanth Mulleti

Pranav Dabral

Zakir Sheikh

John Vivek

Company social profiles

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