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▷ [Apply in 3 Minutes] Data Science (Media Analytics) - 7+ years
4 weeks ago
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, 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.
