Data Scientist

About TuringEdge

TuringEdge

autonomous, goal-driven systems

machine learning, knowledge systems, and multi-agent orchestration

go beyond answers — it should take initiative

That belief drives every platform, product, and partnership we build.

Role Overview

Data Scientist

You’ll collaborate with product engineers, AI architects, and domain experts to turn data into dynamic intelligence — enabling real-world decision automation at scale.

This is a long-term, high-impact role for someone who enjoys blending research with engineering to create scalable, production-ready AI systems.

Key Responsibilities

• Develop, validate, and optimize machine learning models across varied business domains.
• Perform data cleaning, feature engineering, and exploratory analysis to improve model interpretability.
• Collaborate with backend and platform teams to deploy and maintain models in production environments.
• Build reproducible training and evaluation pipelines following 

  MLOps best practices

  .
• Contribute to data-centric initiatives for enterprise digital transformation and modernization.
• Participate in architectural discussions for AI-first product designs and agentic workflows.
• Communicate findings and insights clearly to both technical and non-technical stakeholders.

Required Skills

• Strong experience in 

  Python

  , 

  Pandas

  , 

  NumPy

  , 

  Scikit-learn

  , and 

  PyTorch

   or 

  TensorFlow

  .
• Deep understanding of 

  statistical modeling

  , 

  feature engineering

  , and 

  ML evaluation techniques

  .
• Familiarity with 

  MLOps frameworks

   (MLflow, DVC, Docker, CI/CD pipelines, Git).
• Proficiency in 

  SQL

   and working with structured/unstructured data.
• Exposure to 

  cloud platforms

   such as 

  Azure

  , 

  AWS

  , or 

  Google Cloud

   (Databricks experience is a plus).
• Strong problem-solving mindset and data intuition.
• Excellent written and verbal communication skills.

Preferred / Nice-to-Have

• Experience with 

  LLMs

  , 

  retrieval-augmented generation (RAG)

  , or 

  agent-based AI workflows

  .
• Knowledge of 

  digital twins

  , simulation-based modeling, or reinforcement learning concepts.
• Exposure to 

  data engineering

   tools (Kafka, Airflow, Snowflake, or Delta Lakes).
• Familiarity with 

  LangChain

  , 

  LlamaIndex

  , or vector databases (Pinecone, Weaviate, Redis).

Who You Are

• A problem-solver who enjoys bridging theory and application.
• Someone who thrives in dynamic, research-driven environments.
• Passionate about building intelligent systems that create measurable value.
• Constantly exploring new frameworks and technologies that push AI beyond automation.

Why Join TuringEdge

• Work on end-to-end AI product development — from data pipelines to intelligent orchestration.
• Collaborate with leaders driving enterprise AI modernization and digital-twin strategy.
• Access cutting-edge infrastructure: Azure OpenAI, Databricks, LangGraph, LangChain, and more.
• A culture built on autonomy, innovation, and measurable outcomes.
• Competitive compensation and long-term growth opportunities across multiple AI verticals.

Engagement Details

• Type:

   Full-time (Dedicated Resource)

• Location:

   Remote / Hybrid (India)

• Experience:

   0–3 years

• Compensation:

   Competitive and commensurate with experience

How to Apply

If this sounds like the next step in your AI journey, we’d love to hear from you.

contactus@turingedge.ai

📩 “Application – Data Scientist (AI/ML/MLOps)”

• You can also DM us on LinkedIn — we respond quickly to strong profiles.