Join an innovative Data Science team focused on the Contact Center domain, transforming customer interactions with AI and data-driven intelligence. We specialize in Marketing Analytics, optimizing contact center operations through machine learning, NLP, generative AI, and advanced analytics. Our work involves analyzing customer conversations, predicting user behavior, and enhancing self-service to improve satisfaction and reduce call transfers.

We build advanced conversational AI models, real-time recommendation systems, and predictive analytics solutions that deliver significant business impact. By integrating AI insights with marketing strategies, we facilitate proactive customer engagement, personalized experiences, and operational efficiencies across all touchpoints. This role is crucial for driving strategic initiatives, managing business transformations, and leveraging industry expertise to develop value-driven solutions.

If you are passionate about applying data science to solve complex customer experience challenges, this is an exciting opportunity.

As a Data Science Consultant, you will: - Develop and fine-tune Generative AI models to automate responses and enhance customer interactions. - Build and deploy ML models for intent classification, sentiment analysis, and predictive analytics. - Apply NLP techniques (NER, summarization, embeddings) using frameworks like Hugging Face, LangChain, and OpenAI APIs. - Optimize conversational AI workflows for real-time decision-making and improved self-service. - Analyze large-scale customer interaction data to extract actionable insights. - Work with unstructured data (text, audio, chat, emails) to construct robust AI/ML pipelines. - Collaborate with cross-functional teams (engineering, product, marketing) to integrate AI solutions. - Leverage cloud platforms (Azure, AWS, GCP) for scalable AI/ML development and deployment.

Required Technical Skills include: - Python programming proficiency. - Advanced data manipulation with Pandas and NumPy. - Expertise in SQL or PySpark. - Strong foundation in Machine Learning & Deep Learning (Scikit-learn, PyTorch/TensorFlow). - Proficiency in NLP and NLP Frameworks (NER, summarization, embeddings, Hugging Face, LangChain). - Experience with Generative AI (LLMs, Transformers, Diffusion Models). - Understanding of Retrieval-Augmented Generation (RAG) and Prompt Engineering. - Skills in Unstructured Data Handling.

Good to have skills encompass: - LLM Optimization (fine-tuning, prompt engineering, efficient deployment). - Experience with cloud-native AI/ML services (Azure ML, AWS Sagemaker, GCP Vertex AI). - Customer segmentation and behavioral analysis. - Conversational AI optimization. - Large-scale data analysis. - Agentic AI (multi-agent orchestration, memory, autonomous workflows). - Unstructured Data Handling (audio).

Educational background: Master’s degree in computer science, statistics, applied mathematics, or a related field with 3+ years of experience, OR Bachelor’s degree in computer science, statistics, applied mathematics, or a related field with 4+ years of experience.