Data Science Backend Engineer

3 weeks ago


Kolkata, West Bengal, India Weekday Full time
Backend Data Science Developer

This role is for one of Weekdays clients as a Backend Data Science Developer focusing on Data Science you will be responsible for building optimizing and maintaining serverside applications that support data processing and machine learning models. You will collaborate closely with data scientists data engineers and other developers to create efficient data pipelines scalable APIs and robust backend services that power data driven applications.

Key Responsibilities:
  • Backend Development: Design develop and maintain scalable backend systems services and APIs that handle large datasets and machine learning models.
  • Data Pipeline Integration: Collaborate with data scientists to integrate machine learning models and process large volumes of structured and unstructured data efficiently.
  • API Development: Develop RESTful APIs to expose data science models and data driven services to internal and external applications.
  • Database Management: Design and optimize database structures for storing and querying large datasets ensuring high performance and scalability.
  • Collaboration: Work closely with data engineers data scientists and frontend developers to deliver end to end data solutions.
  • Performance Tuning: Identify bottlenecks and implement solutions for high performance and low latency in data processing systems.
  • Security: Implement security best practices to protect sensitive data and ensure compliance with relevant regulations.
Required Skills and Qualifications:
  • Programming Languages: Proficiency in languages such as Python Java or Node.js.
  • Data Science Integration: Familiarity with integrating data science libraries such as TensorFlow Scikit-learn or PyTorch.
  • API Development: Experience with building and consuming RESTful APIs and microservices architecture.
  • Database Management: Strong knowledge of SQL and NoSQL databases (e.g. PostgreSQL MongoDB).
  • Data Pipeline Tools: Experience with data processing tools and frameworks like Apache Kafka Spark or Hadoop.
  • Cloud Platforms: Experience with cloud environments like AWS GCP or Azure for deploying data centric applications.
  • Version Control: Proficiency with version control systems like Git.
Preferred Skills:
  • Familiarity with containerization (Docker) and orchestration (Kubernetes).
  • Experience with data streaming tools such as Apache Flink or Storm.
  • Strong understanding of machine learning lifecycle and model deployment.
  • Familiarity with data governance privacy laws and data security best practices.

datagovernance aws data science mongodb apache flink storm gcp nosql databases node.js data security azure pytorch spark sql machine learning lifecycle machine learning scikit-learn python restful apis docker java models kubernetes tensorflow hadoop postgresql git apache kafka



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