7 Topic Modeling Jobs

Who We Are Zinnia is the leading technology platform for accelerating life and annuities growth. With innovative enterprise solutions and data insights, Zinnia simplifies the experience of buying, selling, and administering insurance products. All of which enables more people to protect their financial futures. Our success is driven by a commitment to three core values: be bold, team up, deliver value and that we do. Zinnia has over $180 billion in assets under administration, serves 100+ carrier clients, 2500 distributors and partners, and over 2 million policyholders. Who You Are We are seeking a highly motivated Senior Data Scientist with strong technical expertise, business acumen, and strategic problem-solving abilities . In this role, you will independently own and build forecasting models. You will work closely with stakeholders across Product, Data Engineering & Analytics, and Business Strategy to identify opportunities to resolve business problems. This is a high-impact individual contributor role. What Youll Do Work in a dynamic and innovative company to develop cutting-edge solutions. Perform advanced data analytics to influence decision makers. Leverage data from diverse sources to provide insights and build new data driven tools. Partner with engineering teams to continuously improve our data quality. Develop machine learning based applications using supervised and unsupervised models using Python that optimize and personalize customer experiences or reduce manual effort on our internal teams through automated decision making. Develop and support models to enable things such as prescriptive insights, automated decisioning, and insights. Develop experiments to understand model impact, monitor live model analytics, and manage training and retraining pipelines. Work with stakeholders to intake complicated business problems and translate them into solvable data science projects. Partner with data engineering to take your model from development to deployed infrastructure. Brainstorm future use cases and contribute to the learning culture of the data science team. Partner with and mentor other data scientists and data analysts. Partner with multiple marketing teams, manage multiple projects and help conceptualize applications that directly drive company growth and strategy. You will connect machine learning applications to business needs and help facilitate process changes based on algorithmic solution implementation. What Youll Need You have Data Science experience building and validating machine learning and forecasting models in Python for a minimum of 5 years. You love performing advanced analytics to find insights and patterns. You have experience in supervised and unsupervised model techniques such as random forest, gradient boosting, support vector machines, k-means and hierarchical clustering, causal models, mixture models and experience in advanced modeling techniques such as reinforcement learning, neural networks, and natural language modeling. You have experience in delivering natural language projects utilizing techniques such as text summarization, topic modeling, entity extraction, semantic encoding, and valence analysis You have experience working in an agile business setting. You have experience with relational cloud databases like BigQuery and Snowflake and are comfortable working with unstructured datasets such as unstructured text. WHATS IN IT FOR YOU At Zinnia, you collaborate with smart, creative professionals who are dedicated to delivering cutting-edge technologies, deeper data insights, and enhanced services to transform how insurance is done. Visit our website at www.zinnia.com for more information. Apply by completing the online application on the careers section of our website. We are an Equal Opportunity employer committed to a diverse workforce. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability. Show more Show less

As an AI Engineer at GenAI & Applied ML, you will have the opportunity to work with cutting-edge AI technologies, particularly in Generative AI, Large Language Models (LLMs), and applied machine learning. Your role will involve designing, building, and deploying AI solutions using platforms like OpenAI, Hugging Face, and Cohere, specifically for applications in document intelligence, automation, and Q&A systems. You will collaborate with product and engineering teams to integrate AI features into scalable platforms, utilizing tools like Lang Chain, Flask, and AWS/GCP to deploy models effectively. Your key responsibilities will include integrating RAG (Retrieval-Augmented Generation), prompt engineering, and zero/few-shot learning for domain-specific applications, and developing NLP models using advanced techniques such as NER, topic modeling, embeddings (Word2Vec, FastText), and transformers (BERT, GPT). Additionally, you will be automating data extraction, classification, and analysis using Python, Selenium, and web scraping tools, while utilizing frameworks like TensorFlow, PyTorch, and Scikit-learn for training deep learning models across NLP, CV, and recommendation domains. To qualify for this role, you should hold a Bachelor's/masters degree in computer science, AI/ML, Data Science, or related fields, along with at least 1+ years of hands-on experience in building AI/ML models. Proficiency in Python and ML frameworks such as PyTorch, TensorFlow, and Scikit-learn is essential, as well as familiarity with LLM orchestration frameworks, cloud platforms like AWS, GCP, or Azure, and a strong understanding of NLP, Computer Vision, or Recommendation Systems. Experience with SQL, data pipelines, and big data tools like Hadoop and Spark would be advantageous, along with a good understanding of explainable AI (XAI) and model interpretability. Nice to have for this role would be projects or experience in healthcare AI, document processing, or legal/finance AI applications, familiarity with Flask/Django for API development, and contributions to research or published papers in ML/NLP conferences. Join our team and be part of our mission to solve real-world problems through AI innovation and technology.,

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.,

As a NLP & Generative AI Engineer at Gigaforce, you will be part of our dynamic AI/ML team based in Noida, working on cutting-edge technologies to revolutionize the insurance claims processing industry. We are a California-based InsurTech company with a strong focus on innovation and digital transformation in the Property and Casualty sector. You must have a minimum of 2 years of hands-on experience in traditional machine learning, natural language processing, and modern generative AI techniques to be considered for this role. We are looking for individuals who are passionate about deploying GenAI solutions to production, working with open-source technologies, and handling document-centric pipelines efficiently. Your main responsibilities will include building and deploying NLP and GenAI-driven products focusing on document understanding, summarization, classification, and retrieval. You will be designing and implementing models using LLMs such as GPT, T5, and BERT, along with working on scalable, cloud-based pipelines for training, serving, and monitoring models. Collaboration is key at Gigaforce, and you will work closely with cross-functional teams including data scientists, ML engineers, product managers, and developers. Additionally, you will contribute to open-source tools and frameworks in the ML ecosystem, deploying production-ready solutions using MLOps practices, and working on distributed/cloud systems with GPU-accelerated workflows. To be successful in this role, you should have a strong grasp of traditional ML algorithms, NLP fundamentals, and modern NLP & GenAI models. Proficiency in Python, experience with cloud platforms like AWS SageMaker, GCP, or Azure ML, and familiarity with MLOps tools and distributed computing are essential. Experience with document processing pipelines and understanding insurance-related documents is a plus. If you are looking for a challenging role where you can lead the design, development, and deployment of innovative AI/ML solutions in the insurance industry, then this position at Gigaforce is the perfect opportunity for you. Join us in our mission to transform the claims lifecycle into an intelligent, end-to-end digital experience.,

Position : Junior Software Developer Location : Vashi, Navi Mumbai Responsibilities Assist in designing, developing, and testing machine learning models. Work with data engineering teams to collect, clean, and format data for analysis. Implement current machine learning algorithms and experiment with new techniques. Document and present model development processes and results to key stakeholders. Contribute to improving existing AI functionalities within our products. Stay updated with AI/ML advancements and suggest potential integrations. Who We're Looking For Individuals with a strong background in Python, SQL, and a passion for Machine Learning, NLP, and Generative AI. Proficiency in interacting with databases (MySQL) using Python Experience with sentiment analysis, topic modeling, Hugging Face models, RAG, LLM fine-tuning, and Stability AI models. Familiarity with creating and managing APIs, with experience in tools like Swagger for documentation. Fully committed individuals not currently pursuing any academic programs. (ref:hirist.tech),

Role and Responsibilities Develop and fine-tune LLMs using techniques like RAG, transfer learning, or domain-specific adaptation Build AI agents using frameworks like LangChain or CrewAI to manage dynamic and multi-step workflows Work with vector databases (e.g., Pinecone) to enable semantic search and retrieval Design and maintain ETL pipelines and ensure smooth data preprocessing and transformation Implement NLP solutions for tasks like intent detection, sentiment analysis, and content generation Develop backend APIs and services using Python frameworks like FastAPI or Flask Contribute to scalable microservice-based architectures Requirements Bachelor's degree in Computer Science, Information Technology, or a related field. 2 to 4 years in AI/ML development and backend system Machine Learning Fundamentals: Strong grasp of algorithms, model training, evaluation, and tuning Generative AI Models: Experience working with LLMs, RAG architecture, and fine-tuning techniques LangChain or Similar Frameworks: Hands-on experience building AI workflows using toolkits like LangChain Natural Language Processing (NLP): Proficiency in text analytics, classification, tokenization, embeddings Vector Databases: Practical use of tools like Pinecone, FAISS, or similar for retrieval-augmented generation Big Data Handling: Ability to work with large datasets, optimize storage, and processing pipelines SQL/NoSQL: Experience in querying and managing structured and unstructured data Python & API Development: Proficiency in Python and frameworks like FastAPI or Flask ETL & Data Preprocessing: Strong understanding of building pipelines for clean and efficient data processing Soft Skills: Strong problem-solving, communication, and collaboration abilities Good-to-Have Skills: Agentic AI Tools: Exposure to CrewAI or similar platforms for orchestrating multi-agent interactions Content Structuring: Experience in clustering, topic modeling, or organizing unstructured data ETL Enhancements: Advanced optimization techniques for faster and more efficient pipelines Domain Exposure: Prior work on projects involving customer insights, chat summarization, or sentiment analysis

Responsibilities: * Design generative AI solutions using LLM, Python, SQL & NLP techniques. * Collaborate with cross-functional teams on project delivery. * Implement RNN, LSTM, GRU models for text analysis.