Full Stack Data Scientist

1 day ago

Noida, Uttar Pradesh, India KiE Square Analytics Full time ₹ 12,00,000 - ₹ 36,00,000 per year

KiE Square is looking for a passionate and experienced Full Stack Data Scientist to join our Analytics Consulting team. The ideal candidate will possess a strong blend of technical expertise, analytical thinking, and business consulting skills.

You will be responsible for developing and deploying scalable machine learning solutions, building end-to-end data pipelines, and translating analytical insights into actionable business strategies for our clients.

JD :

- Partner with clients to understand business challenges and identify data-driven opportunities.

- Design, build, and deploy end-to-end machine learning models and analytical solutions tailored to client objectives.

- Develop data ingestion, transformation, and modelling pipelines using modern data engineering tools.

- Translate analytical outcomes into clear business insights, dashboards, and recommendations.

- Work closely with consulting teams to integrate analytics into decision-making frameworks.

- Build and maintain production-ready APIs and ML workflows for scalable model deployment.

- Implement MLOps practices for continuous integration, deployment, and performance monitoring.

- Mentor junior team members and contribute to internal best practices in analytics and data science.

- Education : Bachelor's or Master's degree in Data Science, Statistics, Computer Science, Engineering, Economics, or related field.

- Experience : 5 to 7 years in analytics consulting, applied data science, or end-to-end AI/ML solution development.

- Proven experience in problem framing, model development, and production deployment.

- Proficiency in Python (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, etc.) and SQL.

- Hands-on experience with data engineering tools (Airflow, Spark, or Databricks).

- Exposure to cloud environments such as AWS, Azure, or GCP.

- Ability to analyse structured and unstructured data from multiple sources.

- Experience in model interpretability, A/B testing, and business impact measurement.

- Strong client communication, storytelling, and presentation skills.

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