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Engaged Employer

Ernst & Young

Compare

3.4

based on 10.6k Reviews

Video summary

2338 Ernst & Young Jobs

SaT-DnA-Data Science Gen AI Assistant Manager

Ernst Young

3.4

based on 10.6k Reviews

6-8 years

₹ 7.8 - 28L/yr (AmbitionBox estimate)

Bangalore / Bengaluru

1 vacancy

SaT-DnA-Data Science Gen AI Assistant Manager

Ernst & Young

posted 13hr ago

Job Role Insights

Flexible timing

Key skills for the job

Supply Chain Management Consulting Healthcare Automation Testing Business Analytics Telecom

+ 4 more

Job Description

Develop, review, and implement Solutions applying AI, Machine Learning, Deep Learning, and develop APIs using Python.
Having relevant understanding of Big Data and Visualization would be one-upping.
Lead the development and implementation of Generative AI applications using both open source (Llama, BERT, Dolly etc.) and closed source (Open AI GPT models, MS Azure Cognitive Services, Google s Palm, Cohere etc.) Large Language Models (LLMS).
Extensively work with advanced models such as GPT , Llama, BERT, RAG and Graph RAG for natural language processing , and creative content generation using contextual information.
Design and optimize Agentic RAG solutions leveraging Vector databases for efficient storage and retrieval of contextual data for LLMs.
Understand Business and Sectors, ability to identify the whitespaces and opportunities for analytics application.
Work and manage large to mid-size projects, and ensure smooth service delivery on assigned products, engagements and/or geographies.
Work with project managers to study resource needs and gaps and devise alternative ways forward.
Provide expert reviews for all projects within the assigned subject.
Ability to communicate with cross functional/competencies teams.
Go to Market / Stakeholder Management.

Skills and attributes for success

Able to work creatively and systematically in a time-limited, problem-solving environment
Loyal and reliable with high ethical standards
Flexible, curious and creative, open for new things and able to propose innovative ideas
Good interpersonal skills
Team player, open, pleasure to work with and positive in a group dynamic
Intercultural intelligence and experience of working in more than one country and/or multi-cultural teams with distributed delivery experience
Ability to manage multiple priorities simultaneously to meet tight deadlines and drive projects to completion with minimal supervision

To qualify for the role, you must have

Experience of guiding teams on Projects focusing on AI/Data Science and Communicating results to clients
Familiar in implementing solutions in Azure Cloud Framework
Excellent Presentation Skills
6 - 8 years of relevant work experience in developing and implementing Agentic GenAI/AI, Machine Learning Models- experience of deployment in Azure is preferred
Experience in application of statistical techniques like Linear and Non-Linear Regression / classification / optimization , Forecasting and Text analytics.
Familiarity with deep learning and machine learning algorithms and the use of popular AI/ML frameworks
Minimum 4 years of experience in working with NLG, LLM, DL Techniques
Relevant understanding of Deep Learning and neural network techniques
Expertise in implementing applications using open source and proprietary LLM models
Proficient in using Langchain-type orchestrators or similar Generative AI workflow management tools
Minimum of 5-6 years of programming in Python
Experience with the software development life cycle (SDLC) and principles of product development
Willingness to mentor team members
Solid thoughtfulness, technical and problem-solving skills
Excellent written and verbal communication skills

Employment Type: Full Time, Permanent

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What people at Ernst & Young are saying

3.3

Rating based on 373 Assistant Manager reviews

Anonymous · Customer Success, Service & Operations in Hyderabad / Secunderabad

Likes

General shift timing

Dislikes

Worst work culture Micromanagement Working pressure with extended work hours upto 15 hours a day (without additional pay) Not employees centric culture Poor management (not at all adress issues for mostly)