Data Scientist – SDM

Aceolution; Hyderabad; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Aceolution is seeking a Data Scientist – SDM to lead and shape AI-driven initiatives. You will bridge research and business, building production-ready ML and Generative AI solutions while mentoring teams.

You will design systems, optimize LLMs, and drive RAG-based architectures, with a focus on NLG, automation, and decision support across functions.

Qualifications

• Bachelors or Masters in Statistics, Mathematics, CS, Data Science or related quantitative field.
• 10+ years of progressive experience in Data Science, ML, or AI roles.
• Proven enterprise ML/AI deployment experience in production environments.
• Strong Python and/or R proficiency.
• Hands-on with ML frameworks: PyTorch, TensorFlow, Scikit-learn, Hugging Face.

Responsibilities

• Design and optimize advanced ML models, predictive algorithms, and statistical frameworks.
• Lead end-to-end DS lifecycle: data collection, EDA, feature engineering, training, deployment, monitoring.
• Build scalable AI solutions addressing complex business challenges.
• Evaluate models and improve accuracy, reliability, and scalability.
• Lead Generative AI applications and AI-driven products.

Skills

Python

Machine Learning

Generative AI

NLP

Data analysis

Education

Bachelor's or Master's in Statistics/Mathematics/CS/Data Science

Tools

PyTorch

TensorFlow

Scikit-learn

Hugging Face

Job description

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

• 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.
• 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.
• 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.
• 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.
• 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.
• Data Science Leadership
• Generative AI & LLMs
• Retrieval-Augmented Generation (RAG)
• Natural Language Processing (NLP)
• Statistical Modeling
• Predictive & Prescriptive Analytics
• 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.