3 Ccaas Platforms Jobs

At PwC, our team in data and analytics engineering focuses on utilizing advanced technologies and techniques to create robust data solutions for clients. You will be instrumental in converting raw data into actionable insights, empowering informed decision-making, and fostering business growth. If you specialize in artificial intelligence and machine learning, your primary responsibility will be developing and implementing cutting-edge AI and ML solutions to drive innovation and optimize business processes. Your tasks will include designing and refining algorithms, models, and systems to facilitate intelligent decision-making and automation. Candidates with over 15 years of hands-on experience are preferred for this role. **Must Have:** - Knowledge of the CCaaS domain, contact center operations, customer experience metrics, and industry-specific challenges - Understanding of conversational data (chats, emails, and calls) to train Conversational AI systems - Proficiency in CCaaS platforms like NiceCX, Genesys, Cisco, etc., including their architecture, functionalities, and integration capabilities - Familiarity with contact center metrics such as average handle time (AHT), first call resolution (FCR), and customer satisfaction (CSAT) - Understanding of sentiment analysis, topic modeling, and text classification techniques - Proficiency in data visualization tools like Tableau, Power BI, Quicksight, and others - Knowledge of cloud platforms (e.g., AWS, Azure, Google Cloud) and their services for scalable data storage, processing, and analytics - Expertise in NLU Verticals: ASR generation, SSML modeling, Intent Analytics, conversational AI testing, Agent Assist, Proactive Outreach Orchestration, and Generative AI - Application of advanced statistical and machine learning techniques to analyze extensive datasets and create predictive models and algorithms to enhance contact center performance **Nice To Have:** - Proficiency in programming languages such as Python, Pyspark, R, SQL - Strong grasp of data science principles, statistical analysis, and machine learning techniques - Experience in predictive modeling - Skills in regression analysis, time series forecasting, clustering, and NLP techniques - Knowledge of distributed computing frameworks like Hadoop and Spark for processing large data volumes - Understanding of NoSQL databases (e.g., MongoDB, Cassandra) for managing unstructured and semi-structured data - Awareness of data security best practices, encryption techniques, and compliance regulations (e.g., GDPR, CCPA), along with ethical considerations in data science and responsible AI practices **Educational Background:** - BE / B.Tech / MCA / M.Sc / M.E / M.Tech / MBA,

As an Analyst in Customer Experience Management, you will be responsible for collaborating with clients to design and implement strategic customer service initiatives. Your role will involve integrating GenAI capabilities into contact center and self-service solutions, delivering intelligent automation and personalized customer interactions. You will also manage stakeholder expectations, resolve project issues, and implement orchestration platforms for contact center solutions. To excel in this role, you should possess skills in Customer Experience Management, knowledge of CCaaS platforms and Nice CXone, experience with Conversational AI, NLU, NLP, and multichannel applications (SMS, Email, Chat, Web), understanding of contact center infrastructure components and orchestration platforms, familiarity with GenAI integration for automation and personalization, API integrations, Java, WebServices, Containerization (Kubernetes), and experience with auxiliary systems like WFM, Recording, Quality Management. You will lead multichannel self-service and IVR solution design, apply emerging technologies in customer experience and AI, participate in pre-sales activities and solution presentations, and contribute to innovation through reusable assets and market analysis. This role offers the opportunity to work on transformative projects with global clients, exposure to cutting-edge technologies and AI-driven customer experience platforms, and an inclusive and collaborative work environment with career growth opportunities. The ideal candidate for this position should have a minimum of 2 years of experience in delivering voice and non-voice customer interaction solutions using application development tools and implementing customer experience management tools. Additionally, a Bachelors Degree in Engineering (B-Tech/BE), MCA, MBA, or PGDM from a Tier 1 or 2 institution is required.,

As a data and analytics engineering professional at PwC, your primary focus will be on leveraging advanced technologies and techniques to design and develop robust data solutions for our clients. You will play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and ultimately driving business growth. In the realm of artificial intelligence and machine learning, your responsibilities will involve developing and implementing advanced AI and ML solutions to foster innovation and enhance business processes. Your work will encompass designing and optimizing algorithms, models, and systems to facilitate intelligent decision-making and automation. Candidates with 15+ years of hands-on experience are preferred for this role. Essential requirements for this position include familiarity with the CCaaS domain, contact center operations, customer experience metrics, and industry-specific challenges. You should also possess a solid understanding of conversational data (chats, emails, and calls) to train Conversational AI systems. In-depth knowledge of CCaaS platforms such as NiceCX, Genesys, and Cisco, including their architecture, functionalities, and integration capabilities, is crucial. Proficiency in contact center metrics like average handle time (AHT), first call resolution (FCR), and customer satisfaction (CSAT) is necessary. Additionally, familiarity with sentiment analysis, topic modeling, and text classification techniques, as well as proficiency in data visualization tools like Tableau, Power BI, and Quicksight, is required. An understanding of cloud platforms (e.g., AWS, Azure, Google Cloud) and their services for scalable data storage, processing, and analytics is essential. Expertise in NLU verticals such as ASR generation, SSML modeling, Intent Analytics, conversational AI testing, Agent Assist, Proactive Outreach Orchestration, and Generative AI is highly valued. You will also be expected to apply advanced statistical and machine learning techniques to analyze large datasets and develop predictive models and algorithms to enhance contact center performance. Preferred qualifications include proficiency in programming languages such as Python, Pyspark, R, and SQL, as well as a strong understanding of data science principles, statistical analysis, and machine learning techniques. Experience in predictive modeling, along with skills in techniques like regression analysis, time series forecasting, clustering, and NLP techniques, is advantageous. Knowledge of distributed computing frameworks like Hadoop and Spark for processing large volumes of data is beneficial. An understanding of NoSQL databases (e.g., MongoDB, Cassandra) for handling unstructured and semi-structured data is also preferred. Awareness of data security best practices, encryption techniques, and compliance regulations (e.g., GDPR, CCPA), as well as an understanding of ethical considerations in data science and responsible AI practices, will be beneficial. The ideal educational background for this role includes a degree in BE, B.Tech, MCA, M.Sc, M.E, M.Tech, or MBA.,