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.
- Solid 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) (Hyderabad)
🏢 Aceolution India
📍 Hyderabad