Data Scientist at HPE Storage

Job Description

Hewlett Packard Enterprise creates new possibilities for technology to have a meaningful impact on people, businesses, governments and society. HPE brings together a portfolio that spans software, services and IT infrastructure to serve more than 1 billion customers in over six continents. HPE invents, engineers, and delivers technology solutions that drive business value, create social value, and improve the lives of our clients.

Learning does not only happen through training. Relationships are among the most powerful ways for people to learn and grow, and this is part of our HPE culture. In addition to working alongside talented colleagues, you will have many opportunities to learn through coaching and stretch assignment opportunities. You’ll be guided by feedback and support to accelerate your learning and maximize your knowledge. We also have a “reverse mentoring” program which allows us to share our knowledge and strengths across our multi-generation workforce.

HPE makes Hybrid IT simple. HPE helps customers to design the right mix of Hybrid IT to serve their unique needs. We bring next generation infrastructure that uses intelligent software to simplify and accelerate the delivery of new apps, services and business insights. Providing with new ways to deliver and manage IT on-premises and in the cloud.

Responsibilities:

• Identify valuable data sources based on domain knowledge and by working with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
• Undertake pre-processing of structured and unstructured data and perform EDA to discover trends and patterns on large datasets. Optimize the processes for scaling to “Big-Data” scale of dataset.
• Assess the effectiveness and accuracy of data sources and data gathering techniques.
• Build predictive models and machine-learning algorithms on these datasets. Develop custom data models and algorithms , combine models through ensemble modelling etc based on the needs.
• Present information using data visualization techniques for explaining and justifying the models and analysis.
• Develop testing framework for testing model quality. Come up with processes and tools to monitor and analyze model performance and data accuracy.
• Productize the data science work by developing a software for the deployment and hosting of the models for other partner teams to consume. This will include hands-on work in software development including designing and implementation of the solution as well as dev-ops for deployment of the solution.
• Propose solutions and strategies to complex business challenges and be responsible for the end to end conceptualization, development and Productization of the machine learning solution.
• Embrace 'agile' methodologies and deliver within the constructs of an agile SCRUM team.

Education and Experience Required:

• BE/MS in Computer Science from leading engineering institutions in India/abroad. Graduates/PGs of tier1 institutions only(IIT/NIT preferred)
• Typically 8-12 years experience.

Knowledge and Skills:

• Atleast 4-5 years of product development experience in AI led solutions (preferably in the Storage Management software domain) with working experience as a Data Scientist/ on Machine learning
• Hands on experience in application development in languages like Python/ Scala
• Exposure to deployment applications using DevOps tools like Docker, Kubernetes etc
• Must have prior experience with EDA and model development on numeric/metric data
• ML Programming experience in Python/R with extensive hands-on experience of working on Jupyter Notebooks / RStudio/ Zeppelin etc
• Ability to manipulate and visualize data and present your findings independently, hands on experience with Matplotlib, Ggplot, Plotly etc
• Knowledge and hands-on experience of a variety of machine learning techniques (Clustering, Decision Tree learning, Random Forests, Artificial Neural Networks, etc.)
• Knowledge and hands-on experience of advanced statistical techniques and concepts (Regression, properties of distributions, statistical tests and proper usage, etc.)
• Hands on experience in Apache Spark to run jobs to train models on “Big-Data” scale of datasets over data lakes like S3, NFS, HDFS etc
• Exposure with a deep learning framework such as TensorFlow or Keras would be good
• Experience with a database like Cassandra/TimescaleDB etc
• Should be able to handle ambiguity and be open to exploring multiple approaches/variations to arrive at the final solution

We offer:

• A competitive salary and extensive social benefits

• Diverse and dynamic work environment

• Work-life balance and support for career development

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