Senior Data Scientist - Machine Learning Operations & NLP - Media

JD - Sr. Data Scientist

• Experience: 6+ years
• Location: Bangalore (Onsite)
• Notice Period: Candidates who can join within 15 days may only apply

Job Summary

• We are seeking a Senior Data Scientist with strong expertise in MLOps and NLP to support media analytics use cases. The ideal candidate will have hands-on experience in developing and operationalizing advanced machine learning models, maintaining production-grade pipelines, and driving automation across the model lifecycle.

• A minimum of 6 months of experience in media analytics or marketing effectiveness is sufficient, provided there is strong technical depth in model deployment, optimization, and NLP-driven business insights.

Required Skills & Experience

• 6-8 years of experience in Data Science/Analytics with solid exposure to machine learning operations (MLOps) and natural language processing (NLP).
• Bachelor's degree in Computer Science, Data Science, Statistics, Economics, Mathematics, or related quantitative fields. A master's degree is preferred.
• Strong programming skills in Python, Spark, and SQL, following clean coding and documentation best practices.
• Proven experience in MLOps, including CI/CD pipelines, automated testing, containerization, model monitoring, and deployment.
• Experience using platforms such as Databricks, Snowflake, and Azure.
• Familiarity with large language models (LLMs), generative AI, and integrating NLP solutions into business workflows.
• Proficiency with BI tools such as Power BI, Tableau, or DOMO.
• Deep understanding of machine learning algorithms, data structures, and scalable solution design.
• Strong analytical and problem-solving skills with an ability to work in a fast-paced environment.
• Excellent communication and teamwork skills with the ability to collaborate across global teams.

Desired Qualifications:

• Industry background in Retail, eCommerce, or CPG.
• Experience with time series forecasting, customer lifetime value modeling, and text-based classification tasks.
• Familiarity with cloud-native MLOps tools (Azure ML, MLflow, Kubeflow, etc.).

Key Responsibilities

• Design, build, and deploy scalable machine learning and NLP models for various business needs.
• Implement and maintain production-grade MLOps pipelines including model training, testing, deployment, and monitoring.
• Collaborate with stakeholders to translate business challenges into data-driven insights and AI solutions.
• Support limited media analytics use cases, including campaign performance measurement and media optimization.
• Partner with cross-functional teams (data engineers, architects, business analysts) to deliver robust AI and ML solutions.
• Drive automation in data science workflows, performance tracking, and model governance processes.
• Promote the adoption of modern tools, frameworks, and practices for continuous improvement.
• Research and experiment with new technologies such as LLMs and generative AI for practical business applications.