Engr III Cslt-Data Science
Hyderabad, India
- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting
What you’ll work on
Full postingDesign and deploy AI/ML and generative AI solutions for financial operations
Build agentic AI workflows that automate multi-step financial analysis
Write complex SQL/BigQuery queries and data pipelines on GCP and Python
Turn model outputs into clear, actionable insights for finance stakeholders
Implement MLOps practices to monitor financial AI models in production
From the employer’s posting
Design and deploy core AI/ML and Generative AI solutions to optimize financial operations.
Build and orchestrate Agentic AI workflows to automate multi-step financial analysis and decision-making processes.
Engineer robust data pipelines and write complex SQL/BigQuery queries to extract and transform large-scale financial datasets using GCP and Python.
Act as a data storyteller—synthesizing complex AI/ML model outputs into clear, actionable, and prescriptive insights for non-technical finance stakeholders.
Implement MLOps best practices to ensure continuous integration, deployment, and monitoring of financial AI models in production environments.
Education & alternatives
You'll need to have: - Bachelor’s degree in Computer Science, Data Science, Statistics, Mathematics, or a related field - Three or more years of relevant professional work experience.
Even better if you have one or more of the following: - Advanced degree (Master’s) in Computer Science, Statistics, Data Science, or a related field. - Prior experience in the telecommunications industry specifically dealing with financial data, billing systems, FinOps, revenue assurance.
Tools in this posting
- Python
- SQL
- BigQuery
- GCP
Source — Tool mentions in context
- Utilize foundational models and AI assistants (e.g., Claude, GitHub Copilot) to rapidly prototype, iterate, and deliver agile AI solutions to meet dynamic business needs. - Engineer robust data pipelines and write complex SQL/BigQuery queries to extract and transform large-scale financial datasets using GCP and Python. - Act as a data storyteller—synthesizing complex AI/ML model outputs into clear, actionable, and prescriptive insights for non-technical finance stakeholders.
- Experience with all phases of end-to-end Analytics project, such as (but not limited to): Ingestion, Munging, Model Building, Validation, Operationalization, Monitoring - Strong programming proficiency in Python and advanced SQL. - Proven experience working within cloud platforms (Teradata/ GCP) and using tools like BigQuery for large-scale data processing.
- Strong programming proficiency in Python and advanced SQL. - Proven experience working within cloud platforms (Teradata/ GCP) and using tools like BigQuery for large-scale data processing. - Demonstrated experience in rapid prototyping and building solutions leveraging Large Language Models (LLMs) and AI tools (e.g., Claude, Copilot).
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Sep 29, 2026 · 30 days ago
- Recorded sightings
- 103
- Last seen by us
- Oct 30, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Your next step
- Have your resume and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the pay range before committing time to the process.
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Job description
When you join Verizon
You want more out of a career. A place to share your ideas freely — even if they’re daring or different. Where the true you can learn, grow, and thrive. At Verizon, we power and empower how people live, work and play by connecting them to what brings them joy. We do what we love — driving innovation, creativity, and impact in the world. Our V Team is a community of people who anticipate, lead, and believe that listening is where learning begins. In crisis and in celebration, we come together — lifting our communities and building trust in how we show up, everywhere & always. Want in? Join the #VTeamLife.
What you’ll be doing...
As a Consultant (Analytics) you will be a pivotal player in modernizing telecom financial operations. Bridging the gap between implementation and architectural strategy, you will design, develop, and deploy advanced AI/ML, Generative AI, and Agentic AI solutions tailored for the finance domain. Your work will transition complex financial workflows—such as Forecasting as a Service, Explainability framework, Funnel Forecasting, Customer Profitability etc., and also performing analyses that impact Bad Debt, Cash flow, Credit Score cut models, etc., among others—into automated, intelligent, and proactive systems.
You will own the end-to-end lifecycle of critical AI models while translating complex technical results into compelling business narratives for finance leadership.
- Design and deploy core AI/ML and Generative AI solutions to optimize financial operations.
- Build and orchestrate Agentic AI workflows to automate multi-step financial analysis and decision-making processes.
- Utilize foundational models and AI assistants (e.g., Claude, GitHub Copilot) to rapidly prototype, iterate, and deliver agile AI solutions to meet dynamic business needs.
- Engineer robust data pipelines and write complex SQL/BigQuery queries to extract and transform large-scale financial datasets using GCP and Python.
- Act as a data storyteller—synthesizing complex AI/ML model outputs into clear, actionable, and prescriptive insights for non-technical finance stakeholders.
- Design, develop, and optimize Artificial Intelligence, NLP, SLM/LLM solutions to diverse real-world problems.
- Implement MLOps best practices to ensure continuous integration, deployment, and monitoring of financial AI models in production environments.
- Driving data-derived insights across the business domain by developing advanced statistical models, machine learning algorithms and computational algorithms based on business initiatives.
What we’re looking for...
Your primary focus will be transforming traditional financial operations into a proactive, AI-driven organization. You are a hands-on builder who thrives at the intersection of core ML, cutting-edge GenAI, and business strategy. You have a knack for rapid prototyping and possess the communication skills required to explain the "why" and "how" of AI to business leaders.
You'll need to have:
- Bachelor’s degree in Computer Science, Data Science, Statistics, Mathematics, or a related field
- Three or more years of relevant professional work experience.
- Three or more years of experience practicing data science, AI engineering, or machine learning, with a strong focus on core AI/ML, GenAI, and Agentic frameworks.
- Experience with all phases of end-to-end Analytics project, such as (but not limited to): Ingestion, Munging, Model Building, Validation, Operationalization, Monitoring
- Strong programming proficiency in Python and advanced SQL.
- Proven experience working within cloud platforms (Teradata/ GCP) and using tools like BigQuery for large-scale data processing.
- Demonstrated experience in rapid prototyping and building solutions leveraging Large Language Models (LLMs) and AI tools (e.g., Claude, Copilot).
- Hands-on familiarity with specific Agentic AI and orchestration frameworks (e.g., LangChain, LangGraph, LlamaIndex).
- Exceptional data storytelling and communication skills, with a proven ability to translate complex technical concepts into confident financial business decisions.
Even better if you have one or more of the following:
- Advanced degree (Master’s) in Computer Science, Statistics, Data Science, or a related field.
- Prior experience in the telecommunications industry specifically dealing with financial data, billing systems, FinOps, revenue assurance.
- Experience in designing and deploying end-to-end MLOps and LLMOps pipelines.
- A strong understanding of financial forecasting models, anomaly detection algorithms, and time-series analysis.
Why Verizon?
Verizon is committed to maintaining a Total Rewards package which is competitive, valued by our employees, and differentiates us as an Employer of Choice.
- We are a ‘pay for performance’ company and your contribution is rewarded through competitive salaries and performance-based incentives. We create an opportunity for us all to share in the success of Verizon and the value we help to create through this broad-based discretionary equity award program.
- Your benefits are market competitive and delivered by some of the best providers.
- You are provided with a full spectrum of health and wellbeing resources, including a first in-class Employee Assistance Program, to empower you to make positive health decisions.
- We offer generous paid time off benefits to help you manage your work life balance and opportunities for flexible working arrangements*.
- Verizon provides training and development for all levels, to help you enhance your skills and develop your career, from funding towards education assistance, award-winning training, online development tools and access to industry research.
- You will be able to take part in volunteering opportunities as part of our environmental, community and sustainability commitment.
Your benefits package will vary depending on the country in which you work.
*subject to business approval
If Verizon and this role sound like a fit for you, we encourage you to apply even if you don’t meet every “even better” qualification listed above.
Where you’ll be working
In this hybrid role, you'll have a defined work location that includes work from home and assigned office days set by your manager.Scheduled Weekly Hours
40Equal Employment Opportunity
Verizon is an equal opportunity employer. We evaluate qualified applicants without regard to race, gender, disability or any other legally protected characteristics.
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- Location & working pattern
Hyderabad, India
Where you’ll be working In this hybrid role, you'll have a defined work location that includes work from home and assigned office days set by your manager. Scheduled Weekly Hours
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