Virtusa
Gen AI developer
Job Description
Key Business Requirements:
1) Python Experience
2) Bayesian Statistics
3) Ads Measurement (P1), Market mixed modelling exposure
Experience:
Min 2-3 years in each aspect of the above requirements
Data Science Skills
Expertise in analyzing the large data sets (Advertisement related can be a good match), manipulate and clean the data sets by using Python
Strong understanding in developing statistics models, with a focus on Bayesian methods
Development and implementations of market mix modelling (MMM) strategies
Technical Skills:
Analysis of AI model training , data analysis
Experience in working as Data Analyst or similar role
Proven experience working with Python for data analysis and manipulation
Strong understanding of statistical concepts, experience in Bayesian is added advantage
Experience with Data Visualization tools
Excellent skills in Python (most common) or PySpark (for large-scale data processing).
Experience in conceptualizing, designing, validating, and deploying solutions using Large Language Models (LLMs) for content generation or data analysis.
Experience with fine-tuning at least one popular LLM (OpenAI GPT-3, Google AI Gemini, etc.).
Deep understanding of crafting prompts to get the desired outputs from LLMs.
Experience with LLM agents (LangChain) and vector databases (Pinecone, Chroma, FAISS) for efficient LLM interaction.
Soft Skills:
Communicate technical solution in simple manner adhering the existing quality standards.
Interpret and communicate complex data findings to stakeholders in a clear and concise manner
Staying up-to-date on the latest trends and advancements in the advertising measurement, data analysis and LLM space and product
Key Responsibilities:
Ability to debug/reproduce user issues in-code, and develop examples to prove functionality or lack thereof
Provide technical support via emails/forums for the specialized Product Areas
Manage and resolve technical support cases with a high degree of technical complexity for Google Ads products
Respond to customer-reported issues in a timely manner, per service level agreements.
Communicate progress of resolution/status in a timely fashion, per service level agreements
Manage escalations and expectations, for both customers and internal staff.
Timely and Valid escalations of issues to L2 Team.
Timely and Valid routes of issues to other Teams.
Coordinate across numerous departments while driving issues to resolution.
Follow established support processes and procedures.
Work effectively and manage your queue and bugs with minimal supervision.
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