Senior Data Scientist

1 day ago

Noida, Uttar Pradesh, India KiE Square Full time ₹ 20,00,000 - ₹ 25,00,000 per year

KiE Square is looking for a passionate and experienced Sr. Data Scientist to join our Analytics Consulting team. The ideal candidate shall 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.

Responsibilities

  • 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.

Required Skills & Qualifications

  • Education: B.Tech/M.Tech in Computer Science (with Data Science Masters is a plus)
  • Experience: 57 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 on at least two of the top platforms such as Google Vertex AI, Amazon Sagemaker, Azure Databaricks.
  • Proficiency with SaaS LLMs, including Lang chain, llama index, vector databases, Prompt engineering (COT, TOT, ReAct, agents).
  • Hands-on experience with data engineering tools (Airflow, Spark, or Databricks). Techniques such as quantization, LLM finetuning using PEFT, RLHF, data annotation workflow, and GPU utilization.
  • 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.

Good to Have

  • Exposure to data visualization tools such as Power BI, Tableau, AWS Quicksight or Looker.
  • Understanding of consulting frameworks and client delivery models.
  • Familiarity with API development (Flask, FastAPI) and containerization (Docker, Kubernetes).
  • Experience with LLMs or Generative AI use cases is a plus.

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