BR
BrillioPrincipal Data Scientist - R01551388
LocationBangalore, Karnataka, India
Work modehybrid
Typefull-time
SeniorityLead
Experience12+ yrs
DepartmentAI & Data Engineering, AI & Data Engineering : Data Science
Company size5,001–10,000 people
PostedJun 9, 2025 · 1y ago
Verified live1d ago
At a glanceSummarised by Seekless from the posting.
ML & GenAI Expertise – LLMs (GPT, RAG), NLP, Deep Learning
MLOps & Deployment – Model lifecycle management, CI/CD, monitoring
Data Engineering – Scalable data pipelines, big data tools (Databricks/Spark)
Programming – Python, SQL, TensorFlow/PyTorch
Leadership – Team mentoring, AI strategy, stakeholder collaboration
Hypothesis Testing, T-Test, Z-Test, Regression (Linear, Logistic), Python/PySpark, SAS/SPSS, Statistical analysis and computing, Probabilistic Graph Models, Great Expectation, Evidently AI, Forecasting (Exponential Smoothing, ARIMA, ARIMAX), Tools(KubeFlow, BentoML), Classification (Decision Trees, SVM), ML Frameworks (TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, MXNet), Distance (Hamming Distance, Euclidean Distance, Manhattan Distance), R/ R Studio
Bachelor's or Master's Degree in Computer Science, IT, Engineering, or related fields
Overall 12+ years of experience, including 2+ years in delivering AI-powered products
Minimum 2 years of dedicated Product Management experience
At least 1 year of experience with GPT/LLM model development (pre-processing, feature selection, hyper-parameter tuning)
Hands-on experience with Agentic AI and Graph RAG solutions
Skilled in developing and training GPT/LLM models for applications such as chatbots, Q&A systems, and recommendation engines
Strong background in data analysis, pre-processing, feature engineering, and model selection to deliver accurate models efficiently
Continuous monitoring and iteration to improve model accuracy and performance based on feedback
Work closely with cross-functional teams to define product requirements and develop GPT/LLM use cases
Define and align the vision for Data/AI use cases with senior leadership for medium- and long-term goals
Strong analytical, strategic thinking, problem-solving, and project management skills
Exceptional attention to detail, ability to innovate, and address challenges at both macro and micro levels
Skills
Python
SQL
TensorFlow
PyTorch
PySpark
SAS
SPSS
Great Expectation
Evidently AI
KubeFlow
BentoML
Sci-Kit Learn
CNTK
Keras
MXNet
R
R Studio
Databricks
Spark
GPT
RAG
Principal Data Scientist
Primary Skills
•
ML & GenAI Expertise – LLMs (GPT, RAG), NLP, Deep Learning
•
MLOps & Deployment – Model lifecycle management, CI/CD, monitoring
•
Data Engineering – Scalable data pipelines, big data tools (Databricks/Spark)
•
Programming – Python, SQL, TensorFlow/PyTorch
•
Leadership – Team mentoring, AI strategy, stakeholder collaboration.
•
Hypothesis Testing, T-Test, Z-Test, Regression (Linear, Logistic), Python/PySpark, SAS/SPSS, Statistical analysis and computing, Probabilistic Graph Models, Great Expectation, Evidently AI, Forecasting (Exponential Smoothing, ARIMA, ARIMAX), Tools(KubeFlow, BentoML), Classification (Decision Trees, SVM), ML Frameworks (TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, MXNet), Distance (Hamming Distance, Euclidean Distance, Manhattan Distance), R/ R Studio
Job requirements
•
Education: Bachelor’s or Master’s Degree in Computer Science, IT, Engineering, or related fields.
•
Experience:
•
Overall 12+ years of experience, including 2+ years in delivering AI-powered products.
•
Minimum 2 years of dedicated Product Management experience.
•
At least 1 year of experience with GPT/LLM model development (pre-processing, feature selection, hyper-parameter tuning).
•
Technical Expertise:
•
Hands-on experience with Agentic AI and Graph RAG solutions.
•
Skilled in developing and training GPT/LLM models for applications such as chatbots, Q&A systems, and recommendation engines.
•
Strong background in data analysis, pre-processing, feature engineering, and model selection to deliver accurate models efficiently.
•
Continuous monitoring and iteration to improve model accuracy and performance based on feedback.
•
Collaboration & Leadership:
•
Work closely with cross-functional teams to define product requirements and develop GPT/LLM use cases.
•
Define and align the vision for Data/AI use cases with senior leadership for medium- and long-term goals.
•
Soft Skills:
•
Strong analytical, strategic thinking, problem-solving, and project management skills.
•
Exceptional attention to detail, ability to innovate, and address challenges at both macro and micro levels.