Data Scientist

Open Insights; Maharashtra; On-site; INR 1,800,000 - 2,600,000; Full time

Job summary

Open Insights is seeking a Data Scientist specializing in Generative AI and LLMs to lead enterprise engagements. The role focuses on architecture, data preparation for GenAI, and advisory work with C-level clients in a customer-facing services context.

You will guide data scientists, review data environments, and deliver high-impact insights and roadmaps across client organizations. Onsite participation in workshops is required.

Qualifications

• 5+ years of AI/Big Data experience with customer-facing delivery.
• Deep knowledge of Generative AI and model customization.
• Experience with LLMs and deployment tooling.
• Strong communication and stakeholder management skills.
• Experience driving enterprise engagements and workshops.
• Familiarity with GenAI toolchains, Kubernetes, MLOps/AIOps.

Responsibilities

• Lead discussions with C-level audiences and create strategic roadmaps.
• Advise on GenAI engagements including architecture and discovery.
• Plan, organize and run customer workshops and present findings clearly.
• Review data sources, questionnaire responses, and SME interviews.
• Engage data scientists to explore current and future ecosystems.

Skills

Python

R

SQL

Machine Learning

LLMs

MLOps

AIOps

Communication

Lean

Iterative Deployment

GenAI Architecture

Education

Master's degree in ML/Statistics/CS/AI

Industry certifications (Nvidia, Dell, K8, RHEL)

Tools

cnvrg.io

mlflow

Domino

Job description

Open Insights is looking for Data Scientists specializing in Generative AI and LLM’s (Large Language Models) and has a unique skill set that focuses on harnessing the power of advanced AI techniques to generate creative and insightful content.

Responsibilities

• 5+ years of experience working in the fields of Artificial Intelligence and Big Data with 3+ years of progressive professional growth in a customer-facing services delivery role. Ability to lead discussions with C-level customer roles and drive consensus with these audiences. Ability to create strategic roadmaps for customers in this space. Ability to engage data scientists to explore their existing and future ecosystem.
• Deep knowledge of Generative AI, specifically model selection, data preparation for GenAI training, model fine tuning and customization and guardrail implementation. Ability to perform an advisory role on customer engagements in this space.
• Understanding of the GenAI tooling ecosystem including knowledge and experience of Kubernetes, MLOps and AIOps tools.
• Ability to gain customer trust, ability to plan, organize and drive customer workshops and ability to present findings back to the customer in a coherent, concise, and persuasive way.
• Ability to influence and interact with confidence and credibility at all levels with our customers, partners, and vendors.
• Ability to articulate complex concepts, build consensus and deliver high quality work products.
• Ability to drive engagements related to GenAI architectural analysis, benefits analysis, and discovery.
• The ability to:
  • Receive and review configuration material related to the in-scope areas to gain a clear understanding of the current data and analytics environment that might relate to GenAI use cases.
  • Review questionnaire responses, conduct stakeholder interviews, and discussions with subject-matter experts (SMEs) within the Customer’s organization.
  • Gather information relating to the overall goals and objectives of the organization,
• and their applicability to IT projects and initiatives.
• Proven experience with client facing professional services delivery from presentations, documentation, workshops, and interviews to full scale enterprise-wide technology services delivery.
• Experience working on project teams within a defined methodology while adhering to margin, planning and SOW requirements.
• Ability to be onsite during customer workshops.

Skills And Requirements

• Proficiency with statistical computer languages such as R or Python.
• Proficiency with relational database systems (SQL) and object-based data stores.
• Advanced applied statistics skills, such as distributions, statistical testing, regression, etc.
• Professional experience with machine learning techniques and how to apply them in real-world scenarios.
• Excellent verbal and written communication skills.
• Drive to learn new technologies, statistical methods and data manipulation techniques.
• Understand business context and challenges and articulate practical solutions.
• Strong problem-solving skills with an emphasis on product development
• Experience and deep knowledge of Large Language Models (LLM).
• Hands-on experience with MLOps and AIOps tools such as cnvrg.io, mlfow and Domino.
• Experience using Lean and Iterative Deployment Methodologies.

Preferred

• Master’s degree in Machine Learning, Statistics, Mathematics, Computer Science or Artificial Intelligence.
• In possession of relevant industry certifications e.g. Nvidia, Dell, K8 and RHEL.
• Experience with distributed data systems such as Apache Hadoop or Apache Spark.
• Expertise in analyzing large, complex, multi-dimensional datasets with a variety of tools.
• Familiarity with Agile / Scrum development practices.
• Immediate joiners are preferred