We are seeking a highly skilled and experienced Data Scientist – SDM to join our growing team. The ideal candidate will be a data-driven innovator with deep expertise in machine learning, advanced analytics, statistical modeling, and Generative AI technologies. This role requires a strategic thinker capable of transforming complex data into actionable insights and scalable AI-powered solutions that drive business growth.

As a senior technical leader, you will bridge the gap between advanced research and real-world business applications, leading the development of machine learning models, Generative AI solutions, and intelligent systems while mentoring data scientists and collaborating with cross-functional stakeholders.

Key Responsibilities

Machine Learning & Model Development

Design, develop, and optimize advanced machine learning models, predictive algorithms, and statistical frameworks.
Lead the end-to-end data science lifecycle, including data collection, exploratory data analysis, feature engineering, model training, deployment, and monitoring.
Build scalable and production-ready AI solutions to address complex business challenges.
Evaluate model performance and continuously improve accuracy, reliability, and scalability.
Identify and mitigate model biases, data quality issues, and performance bottlenecks.

Generative AI & Large Language Models (LLMs)

Lead the design, development, and deployment of Generative AI applications and AI-driven products.
Fine-tune and optimize Large Language Models (LLMs) for domain-specific business use cases.
Architect and implement Retrieval-Augmented Generation (RAG) frameworks and intelligent knowledge systems.
Develop advanced Natural Language Processing (NLP) solutions for automation, content generation, search, and decision support.
Evaluate emerging AI technologies and recommend innovative approaches to enhance business capabilities.

Data Science Strategy & Business Impact

Partner with business leaders to identify high-value AI and analytics opportunities.
Translate complex analytical findings into clear, actionable recommendations for stakeholders across Product, Marketing, Operations, Finance, and Leadership teams.
Define key performance indicators (KPIs) and success metrics for AI initiatives.
Drive data-driven decision-making through predictive and prescriptive analytics.
Ensure alignment between business objectives and technical solution design.

Leadership & Mentorship

Mentor, coach, and guide data scientists, machine learning engineers, and analytics professionals.
Establish best practices for experimentation, model development, code quality, and AI governance.
Conduct technical reviews and provide architectural guidance for AI and ML projects.
Foster a culture of innovation, collaboration, and continuous learning.
Support talent development and contribute to building high-performing AI teams.

MLOps & Productionization

Collaborate with Engineering and DevOps teams to deploy, monitor, and maintain machine learning models in production environments.
Improve and scale MLOps workflows, model monitoring frameworks, and deployment pipelines.
Drive automation of model lifecycle management and continuous integration/continuous deployment (CI/CD) processes.
Ensure reliability, security, and scalability of deployed AI systems.

Communication & Stakeholder Management

Present complex technical concepts, model outcomes, and business recommendations to executive leadership and non-technical stakeholders.
Create technical documentation, model evaluation reports, and solution architecture documents.
Act as a trusted advisor and subject matter expert in Data Science, Machine Learning, Generative AI, and Responsible AI practices.
Collaborate with cross-functional teams to drive successful project delivery.

Research & Innovation

Stay current with emerging trends, academic research, and advancements in Machine Learning, Generative AI, NLP, and Data Science.
Evaluate and experiment with new technologies, frameworks, and methodologies.
Promote innovation and adoption of best-in-class AI solutions across the organization.

Required Qualifications

Bachelor's or Master's degree in Statistics, Mathematics, Computer Science, Data Science, Physics, Economics, Engineering, or a related quantitative discipline.
10+ years of progressive experience in Data Science, Machine Learning, or AI-related roles.
Proven experience delivering enterprise-scale machine learning and AI solutions in production environments.
Strong proficiency in Python and/or R programming.
Hands-on experience with machine learning frameworks such as PyTorch, TensorFlow, Scikit-learn, Hugging Face, or similar technologies.
Deep understanding of statistical modeling, predictive analytics, experimentation, A/B testing, and causal inference.
Experience working with large-scale datasets, distributed computing platforms, and data warehousing environments.
Strong problem-solving, analytical, and critical-thinking skills.
Excellent communication and presentation skills with the ability to explain complex technical concepts to diverse audiences.
Demonstrated leadership experience in mentoring teams and driving technical initiatives.

Preferred Qualifications

Experience designing and deploying Generative AI, LLM, and RAG-based applications.
Experience with cloud platforms such as Google Cloud Platform (GCP), Vertex AI, AWS, or Azure.
Strong understanding of MLOps frameworks, CI/CD pipelines, and model lifecycle management.
Experience with distributed computing technologies such as Apache Spark.
Prior experience working within Google or PLX environments.
Knowledge of AI governance, Responsible AI, AI safety, data privacy, and data security best practices.
Experience with vector databases, embeddings, prompt engineering, and LLM evaluation frameworks.

Key Competencies

Data Science Leadership
Machine Learning
Generative AI & LLMs
Retrieval-Augmented Generation (RAG)
Natural Language Processing (NLP)
Statistical Modeling
Predictive & Prescriptive Analytics
MLOps & Model Deployment
AI Strategy & Innovation
Data-Driven Decision Making
Technical Leadership & Mentoring
Stakeholder Management
Executive Communication
Problem Solving & Critical Thinking

Why Join Us

Lead cutting-edge AI and Machine Learning initiatives with real business impact.
Work on advanced Generative AI and Large Language Model applications.
Collaborate with talented engineers, data scientists, and business leaders.
Influence strategic decisions through data-driven innovation.
Be part of a culture that values continuous learning, experimentation, and technological excellence.

Data Scientist SDM