Lead - Data Scientist

Location: Prakāshamnagar

Organizations everywhere struggle under the crushing costs and complexities of 'solutions' that promise to simplify their lives. To create a better experience for their customers and employees. To help them grow. Software is a choice that can make or break a business. Create better or worse experiences. Propel or throttle growth. Business software has become a blocker instead of ways to get work done.
There's another option. Freshworks. With a fresh vision for how the world works.

At Freshworks, we build uncomplicated service software that delivers exceptional customer and employee experiences. Our enterprise-grade solutions are powerful, yet easy to use, and quick to deliver results. Our people-first approach to AI eliminates friction, making employees more effective and organizations more productive. Over 72,000 companies, including Bridgestone, New Balance, Nucor, S&P Global, and Sony Music, trust Freshworks' customer experience (CX) and employee experience (EX) software to fuel customer loyalty and service efficiency.

And, over 4,500 Freshworks employees make this possible, all around the world.
Fresh vision. Real impact. Come build it with us.

Job Description

As a Lead Data Scientist with a focus on Generative Artificial Intelligence (GenAI), you will be at the forefront of pioneering innovative applications of data science and machine learning in employee engagement. You will lead efforts to leverage GenAI techniques to solve complex challenges, transitioning the next generation of IT services away from traditional dashboards and filters into an interactive, conversational experience backed by real-time streaming data analysis.
The Impact You Will Create

You will not just be building models; you will be reshaping how users interact with technology. Your work will directly result in:
Massive Scale:  Building a state-of-the-art conversational service bot designed to scale seamlessly across 1 million+ Monthly Active Users (MAU).
Next-Gen User

Experience:

Serving real-time insights to customers through a cutting-edge conversational UI/UX that processes millions of streaming data points.
Advanced Automation:  Developing production-grade AI/ML solutions to solve complex Text2

Action problems and analyzing time-series data to detect anomalous behavior instantly.

Roles & Responsibilities

Strategic

Collaboration:

Partner closely with product and business teams to deeply understand challenges and opportunities within the GenAI landscape, ensuring data science initiatives align with core organizational objectives.
Intelligent System Design:  Conceptualize, experiment, and design intelligent systems powered by GenAI, applying your deep expertise in machine learning, statistics, and advanced mathematics.
End-to-End ML Pipelines:  Take full ownership of ML pipelines from start to finish, encompassing data pre-processing, model generation, cross-validation, and continuous feedback integration.
ML/AI Architecture:  Collaborate with ML Engineers to design highly scalable systems and model architectures that enable low-latency, real-time ML/AI services.
Big Data Processing:  Build and develop efficient systems capable of ingesting and processing vast volumes of streaming data.
Metric Definition:  Define and monitor key performance metrics that accurately reflect the tangible value delivered to end-users through our GenAI solutions.

Qualifications

Qualifications

Education:

A Bachelor's degree or higher in Computer Science, Statistics, Mathematics, or a highly related quantitative field.

Experience:

A minimum of 7 years of relevant industry work experience.
Production Deployment:  A proven track record of successfully deploying ML projects into production systems, backed by substantial individual contributions.
Key Skills

Mathematical Foundations:  Profound understanding of the math underpinning machine learning algorithms, including probability, statistics, linear algebra, calculus, and optimization.
GenAI & NLP:  Hands-on experience with Natural Language Processing tasks utilizing prompt engineering, Large Language Models (LLMs), transformers, and knowledge graphs.
Big Data & Distributed Computing:  Proficiency in large-scale…