Data Scientist

About Us

Asper.ai, a Fractal company, enables interconnected and automated decisions at the intersection of demand and supply. By changing how decisions are made, Asper.ai unlocks growth and transforms organizations into adaptive, intelligent enterprises. Through its ‘automatic decisioning’ platform, Asper.ai works with data to provide proactive, interconnected, and automated decisions that help customers reach their true potential – from optimizing workflows to growing the bottom line.

This role focuses on improving system reliability and learning through applied research. It requires framing decision-making problems as learning and optimization tasks, designing experiments, and translating research insights into deployable improvements. The role strengthens the system’s ability to reason, adapt, and improve over time.

Why work with us?

• Experience a fast paced, growing, and stable start-up with a culture of care at heart. You will be enabled to be your best every day – personally & professionally.

• Be a part of the AI revolution and bring to life solutions that make a difference to the world.

• Coming to work will not feel monotonous – you get to work with some of the brightest and the nicest colleagues you will meet and build bonds for life. We work hard and have fun together as well.

Key Responsibilities

• Conduct core scientific research to improve agentic reasoning reliability and learning.
• Define agent–environment–reward formulations for decision intelligence workflows.
• Frame learning problems using Deep Reinforcement Learning , preference learning, or supervised fine-tuning .
• Design and evaluate reasoning paradigms such as Chain-of-Thought , Tree-of-Thought , and multi-step planning .
• Curate datasets for training and evaluating reasoning agents.
• Contribute to knowledge system learning , including graph updates and ontology refinement .
• Collaborate closely with AI Engineers to translate research outcomes into production systems.

Education

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
• Advanced degrees or strong academic research background is a plus.

Experience

• 2–6+ years of experience in Data science, Applied research, or ML engineering roles.
• Hands-on experience with deep learning or reinforcement learning projects.

Skills & Expertise

• Strong proficiency in PyTorch / TensorFlow and deep learning frameworks.
• Working knowledge of reinforcement learning algorithms (MDPs, PPO, DPO, GRPO, etc.).
• Experience with transformers, LLM fine-tuning (SFT, LoRA, QLoRA).
• Solid understanding of classical ML and statistical learning concepts.
• Strong analytical and experimental design skills.

Personal Attributes (Must Haves)

• Strong scientific curiosity and problem-solving mindset.
• Ability to balance research depth with practical impact.
• Comfortable working on open-ended problems.