Lead Data Scientist

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 servicebot 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 Text2Action problems and analysing time-series data to detect anomalous behaviour instantly.
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 organisational objectives.
Intelligent System Design: Conceptualise, 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.
Requirements:
A Bachelor's degree or higher in Computer Science, Statistics, Mathematics, or a highly related quantitative field.
A minimum of 7 years of relevant industry work experience.
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 optimisation.
GenAI & NLP: Hands-on experience with Natural Language Processing tasks utilising prompt engineering, Large Language Models (LLMs), transformers, and knowledge graphs.
Big Data and Distributed Computing: Proficiency in large-scale computing and Big Data technologies, specifically distributed programming frameworks like Hadoop and Spark.
Data Engineering: Strong proficiency with database systems and schema design, encompassing both SQL and NoSQL databases.
Domain Expertise: A solid background in at least two of the following specialised areas: Natural Language Processing (NLP), Statistical ML techniques, Deep Learning, Distributed Systems, Graph algorithms, Constraint optimisation, Signal processing (speech or vision)
Core Competencies: Exceptional problem-solving and programming skills.

Experience
6-10 yrs