Banyan Cloud | Data Science Engineer | hyderabad

1 month ago

hyderabad, India Banyan Cloud Full time

About US


Honest Data technologies Pvt Ltd, is a wholly owned subsidiary of Banyan Cloud, USA, the Cyber Security Product Company, headquartered in San Jose, California, USA, owning the SaaS product “Banyan Cloud”, first of its kind Cyber Security CNAP Platform that simplifies the code to cloud security for multi cloud & On-premises environments.


It's a once-in-a-lifetime opportunity to join our rocket ship start-up run by a world-class executive team. We are looking for candidates that aspire to be a part of the cutting-edge solutions and services we offer that address the advance cybersecurity challenges.


Job Description Summary:


We are looking for a “Data Science Engineer” to join our development team based out of Bangalore, which empowers the next generation SaaS application on Hybrid Cloud platform. who are passionate about solving real business problems through innovation and engineering practices. You'll be required to apply your depth of knowledge and expertise to all aspects of the software development life-cycle. Have a thirst to learn new technologies and update themselves to find new solutions to meet the needs of our constantly growing business.


Responsibilities :


As a Data Science Engineer, you will be juggling responsibilities in the data science, data engineering and Gen AI domains. You will also be responsible for:

  • Design, implement and maintain robust data ingestion and extraction pipelines.
  • Manage data infrastructure, including data warehouses, data lakes, and cloud platforms.
  • Ensure data quality, consistency, and security throughout the data lifecycle.
  • Develop and maintain scalable data pipelines using automation tools.
  • Implement data governance policies and procedures.
  • Conduct exploratory data analysis to identify patterns, trends, and anomalies.
  • Develop and train machine learning models using appropriate algorithms to complete POCs.
  • Evaluate model performance and take POCs to production environments.
  • Fine tune and improve Gen AI models to serve business needs.
  • Communicate data insights and findings to stakeholders in a clear and concise manner.
  • Stay up to date with the latest advancements in data science and machine learning.
  • Working with cross-functional teams to assess data science use cases and to understand data and analytics related requirements and define potential projects.
  • Ensure assigned deliverables are completed end-to-end.


Requirements:


  • Bachelor /Master's degree from a top-tier institute, ideally in quantitative discipline (Engineering, Computer Science, Data Science, Economics, Mathematics or similar field).
  • 2-4 years of experience in a data science or data engineering team.
  • Strong understanding of Machine learning fundamentals.
  • Strong knowledge of supervised algorithms. Familiarity with regression, decision trees, random forests and XG boost algorithms.
  • Familiarity with unsupervised algorithms is a plus.
  • Experience with prompt engineering, LLM fine tuning and embedding data into vector databases to develop and improve RAG models.
  • Experience in working with cloud platforms such as AWS and Azure.
  • Excellent planning and execution skills with proven ability to drive results.
  • Strong interpersonal and communication skills and are adept at working with multiple stakeholders to drive desired outcomes.
  • Possess strong analytical skills and are comfortable dealing with numerical data.
  • Pay strong attention to detail and deliver work that is of a high standard.
  • A strong passion for data science and an ever-learning attitude


Tools, libraries and Technologies:


  • Python, sql, pyspark, mongodb, S3, Blob Storage, IAM, Cloudwatch
  • Pandas, numpy, Scikit-learn
  • Langchain, Mongodb vector db, FAISS vector db or other RAG frameworks



Banyan Cloud provides equal employment opportunity (EEO)

Banyan cloud provides equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, pregnancy, sexual orientation, gender identity and/or expression,

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