Data science (media analytics) - 7+ years

JD – Sr. Data Scientist - Media Analytics Experience :  7–8 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 7–8 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, e Commerce, 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.