AI Data Scientist - Machine Learning & Agent-Based Systems

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AI Summary

Join Nova Kore as a data scientist to support the development of advanced analytics and data-driven infrastructure for AI lab partner focused on intelligent agent-based systems. Design and implement robust data models, pipelines, and metrics that support experimentation, benchmarking, and continuous learning for agentic AI systems. Collaborate with engineers to design evaluation frameworks and prototype data-driven feedback loops.

Key Highlights
Design and implement robust data models, pipelines, and metrics
Develop data collection and preprocessing pipelines
Build and iterate on machine learning models
Conduct statistical analyses to evaluate AI system performance
Collaborate with engineers to design evaluation frameworks
Prototype data-driven feedback loops
Technical Skills Required
Python SQL Pandas NumPy Scikit-learn PyTorch TensorFlow
Benefits & Perks
USD 14/hour
Remote work
Flexible working hours
Weekly bonus ranging from $500 to $1,000 USD per five tasks created

Job Description


I’m helping Nova Kore find a top candidate to join their team flexible for the role of AI Data Scientist - Machine Learning & Agent-Based Systems.


You will shape the future of intelligent agent systems through advanced data science and machine learning.


Compensation:

USD 14/hour


Location:

Remote: India


Mission of Nova Kore:

"Connecting people and companies to create meaningful, transformative career and business opportunities."


What makes you a strong candidate:

  • You are proficient in Statistical modeling, SQL, Python, Machine learning, Data science.
  • English - Conversational


Responsibilities and more:

Data scientist - India


The company is hiring a data scientist to support the development of advanced analytics and data-driven infrastructure for an AI lab partner focused on intelligent agent-based systems. This role is suited for analytical professionals who excel at transforming large-scale data into actionable insights and enjoy working at the intersection of machine learning, experimentation, and real-world applications. The position involves designing data pipelines, statistical models, and performance metrics that contribute to the evolution of autonomous systems.


The ideal candidate has a strong background in data science, machine learning, or applied statistics, and is proficient in Python and SQL, with experience using libraries such as Pandas, NumPy, Scikit-learn, and PyTorch or TensorFlow. The role requires an understanding of probabilistic modeling, statistical inference, and experimentation frameworks, including A/B testing and causal inference. Experience in collecting, cleaning, and transforming complex datasets into structured formats for modeling and analysis is essential.


Primary goal of the role


* Design and implement robust data models, pipelines, and metrics that support experimentation, benchmarking, and continuous learning for agentic AI systems.


Key responsibilities


* Develop data collection and preprocessing pipelines for structured and unstructured data from multiple agent simulations.

* Build and iterate on machine learning models for performance prediction, behavior clustering, and outcome optimization.

* Design and maintain dashboards and visualization tools to monitor agent performance, benchmarks, and trends.

* Conduct statistical analyses to evaluate AI system performance across different environments and constraints.

* Collaborate with engineers to design evaluation frameworks that measure reasoning quality, adaptability, and efficiency.

* Prototype data-driven feedback loops to improve model accuracy and agent behavior over time.

* Work closely with AI research teams to translate experimental results into scalable, production-grade insights.


Work structure and compensation


* Hourly contractor role.

* Weekly payment via Stripe Connect based on hours logged.

* Part-time commitment of 20 to 40 hours per week.

* Fully remote and asynchronous schedule with flexible working hours.

* Weekly bonus ranging from $500 to $1,000 USD per five tasks created.


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