Data Scientist

Description : Role : Senior II Data Scientist, Generative AI & Advanced ML

Job Summary :

We are seeking a highly experienced and technically proficient Data Scientist - Senior II to drive innovation at the core of our intelligent systems. This role is a unique blend of cutting-edge Generative AI research, advanced Machine Learning (ML) model development, and technical leadership. The Senior II Data Scientist will be responsible for tackling high-impact business challenges by leading end-to-end ML projects from foundational research and model design through to production deployment. A critical component of this role is mentoring and technically guiding junior team members, shaping the future talent within the data science organization.

Core Responsibilities :

Advanced ML Research and Implementation :

- Conduct in-depth machine learning research, continuously monitoring and evaluating state-of-the-art advancements, particularly in the Generative AI domain (LLMs, Diffusion Models, etc.).

- Read, interpret, and rapidly implement complex methodologies described in academic and industry research papers, translating theoretical concepts into practical, working solutions.

- Design, build, and rigorously evaluate sophisticated machine learning and deep learning models to address complex, high-value business problems across the organization.

- Drive the entire end-to-end ML project lifecycle, from initial hypothesis formulation and data exploration to model deployment, monitoring, and iterative improvement in a production environment.

Generative AI and LLM Development :

- Apply deep familiarity with Transformer architectures and large-scale model optimization techniques to work directly with Large Language Models (LLMs).

- Utilize and build upon orchestration frameworks like Langchain or LlamaIndex to design and engineer robust, production-ready LLM-based applications and autonomous agents.

- Focus on pushing the boundaries of what is possible with data, specifically enabling new levels of insight, innovation, and decision-making capabilities within intelligent systems.

Technical Leadership and Collaboration :

- Actively mentor and guide junior data scientists and interns, providing technical direction, design feedback, and support in executing real-world projects.

- Work collaboratively across engineering, product, and business teams to effectively turn data into decisions and models into high-value products.

- Ensure the successful transition of theoretical models into production-ready code that meets enterprise standards for clarity, precision, performance, and security.

Required Qualifications :

Experience : 5 to 7 years of dedicated, progressive experience in Data Science or Machine Learning roles, with a proven track record of increasing responsibility.

Statistical and Analytical Foundation : Strong foundation in Statistics and Probability, essential for model validity, experimental design, and interpretation of results.

Programming and Libraries :

- Advanced proficiency in Python for scientific computing, data manipulation, and building complex ML workflows.

- Hands-on, expert-level experience with core data science and deep learning libraries, including Scikit-learn, Keras, TensorFlow, and PyTorch.

Algorithm Expertise :

- Expertise in core ML algorithms such as Linear/Logistic Regression, Decision Trees, Gradient Descent methods, Support Vector Machines (SVMs), and ensemble techniques.

- Proven ability to select, adapt, and optimize algorithms for specific business goals.

Generative AI/LLM Specialization :

- Deep familiarity with Transformer architectures and practical experience in fine-tuning, prompt engineering, and working with pre-trained LLMs.

- Practical experience with Langchain or LlamaIndex for building sophisticated, retrieval-augmented generation (RAG) or multi-step reasoning applications.

MLOps Mindset : Proven ability to manage the operational aspects of ML models, including versioning, continuous training, and serving models in a low-latency production environment.

Preferred Skills :

- Experience with cloud-based ML platforms and services (AWS SageMaker, Google Vertex AI, or Azure ML).

- Prior experience publishing technical research or contributing to open-source projects in the AI/ML space.

- Working knowledge of Big Data technologies such as Spark/PySpark for handling and processing massive datasets.

- Advanced specialization in a specific deep learning area, such as Computer Vision (CV), Natural Language Processing (NLP), or time-series forecasting.

- Demonstrated ability to conduct A/B testing and design causal inference experiments.