Staff Data Scientist

5 days ago


Bengaluru, Karnataka, India Auxia Full time

Auxia is building the
Agentic Customer Journey Orchestration Platform
, redefining how enterprises activate, engage, and retain their customers through intelligent, adaptive AI systems. Backed by
$23.5M in funding
from top-tier investors — VMG Technology Partners, Stage 2 Capital, and MUFG Innovation Partners — we're on a mission to make every enterprise truly intelligent.

Our founders,
Sandeep Menon (ex-VP Marketing, Google)
and
Ravi Desu (ex-Global Engineering Lead, WhatsApp Payments @ Meta)
, are building Auxia with the same ambition and technical excellence that powered global platforms used by billions.

Today, Auxia powers
3B+ daily events
,
6,500 queries per second
, and
250M+ decisions per day
, helping global enterprises like
DOCOMO, Mercari, and MUFG
unlock the full potential of their first-party data.

Your Impact

You won't just be joining a data science team — you'll be shaping the future of autonomous, AI-driven personalization. As a
Staff Data Scientist
, you'll lead innovation at the intersection of recommender systems, causal inference, reinforcement learning, and LLM-based personalization. Your work will directly influence how millions of end-users experience hyper-personalized content in real time.

What You'll Do


• Architect and advance large-scale recommender and ranking models powering adaptive customer journeys.


• Design and deploy autonomous agents that understand goals, make real-time decisions, and continuously optimize engagement.


• Partner with engineering and product leaders to translate cutting-edge AI research into scalable systems.


• Lead experimentation frameworks that bridge causality, personalization, and business impact.


• Mentor across teams — setting the data science bar for both experimentation and productization.


• Stay ahead of the curve by bringing ideas from academia and industry research into production.

What You Bring


• M.Tech/PhD or related course in Computer Science, Machine Learning, or a related field.


• 10+ years of experience building and deploying production ML systems at scale.


• Deep expertise in personalization, ranking, recommendation, causal inference, and transformers.


• Mastery of PyTorch / TensorFlow / JAX, and the Python data ecosystem (NumPy, Pandas, SciPy).


• Strong applied experience with LLMs, RAG, information retrieval, and reinforcement learning.


• Strong product sense, with the ability to balance research depth and real-world impact.


• An entrepreneurial, ownership-driven mindset — the ability to ship, iterate, and scale models fast.

Why Auxia



Impact
– Be at the forefront of Agentic AI, driving the evolution of enterprise personalization — from manual segmentation to self-learning systems.



Influence
– Work directly with Auxia's founders and leadership team, alongside ex-Google, Meta, and Lyft engineers. Your insights will shape both our roadmap and the future of enterprise AI.



Growth
– A pivotal role in a high-growth AI company scaling rapidly across the U.S. and Japan, with exposure to Fortune 500 customers and industry-defining challenges.



Work Environment

➜ 100% Onsite, Bellandur, Bangalore (5 days/week) – because innovation thrives in collaboration.

➜ Fast-moving, research-driven environment where ideas turn into production within weeks.

➜ A team that believes in freedom with accountability — great minds solving hard problems, together.



Diversity, Equity & Inclusion

At Auxia, we are committed to building a workplace that celebrates diversity, fosters inclusion, and ensures equal opportunity. We welcome applicants from all backgrounds, regardless of race, gender, religion, age, sexual orientation, or disability.

Ready to Join the Journey?

Auxia is not just a company — it's a movement to make every customer interaction intelligent, adaptive, and human.

If you're driven by deep technical challenges, global impact, and the chance to build with some of the sharpest minds from Google, Meta, and Lyft, this is your next big leap.



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