Graduate degree in a quantitative field (CS, statistics, applied mathematics, machine learning, or related discipline)
- Good programming skills in Python with strong working knowledge of Python's numerical, data analysis, or AI frameworks such as NumPy, Pandas, Scikit-learn, etc.
- Experience with LMs (Llama (1/2/3), T5, Falcon, Langchain or framework similar like Langchain)
- Candidate must be aware of entire evolution history of NLP (Traditional Language Models to Modern Large Language Models), training data creation, training set-up and finetuning
- Candidate must be comfortable interpreting research papers and architecture diagrams of Language Models
- Candidate must be comfortable with LORA, RAG, Instruct fine-tuning, Quantization, etc.
- Predictive modelling experience in Python (Time Series/ Multivariable/ Causal)
- Experience applying various machine learning techniques and understanding the key parameters that affect their performance
- Experience of building systems that capture and utilize large data sets to quantify performance via metrics or KPIs
- Excellent verbal and written communication
- Comfortable working in a dynamic, fast-paced, innovative environment with several ongoing concurrent projects.
Roles & Responsibilities:
- Lead a team of Data Engineers, Analysts and Data scientists to carry out following activities:
- Connect with internal / external POC to understand the business requirements
- Coordinate with right POC to gather all relevant data artifacts, anecdotes, and hypothesis
- Create project plan and sprints for milestones / deliverables
- Spin VM, create and optimize clusters for Data Science workflows
- Create data pipelines to ingest data effectively
- Assure the quality of data with proactive checks and resolve the gaps
- Carry out EDA, Feature Engineering & Define performance metrics prior to run relevant ML/DL algorithms
- Research whether similar solutions have been already developed before building ML models
- Create optimized data models to query relevant data efficiently
- Run relevant ML / DL algorithms for business goal seek
- Optimize and validate these ML / DL models to scale
- Create light applications, simulators, and scenario builders to help business consume the end outputs
- Create test cases and test the codes pre-production for possible bugs and resolve these bugs proactively
- Integrate and operationalize the models in client ecosystem
- Document project artifacts and log failures and exceptions.
- Measure, articulate impact of DS projects on business metrics and finetune the workflow based on feedbacks
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