1 to 25 of 48 Permanent Sentiment Analysis Jobs

Strong analytical thinking skills to interpret data and derive actionable insights. Ability to translate complex data science concepts into simple, understandable results for non-technical stakeholders. Proficiency in statistical analysis, hypothesis testing, and predictive modeling. Experience working with healthcare or finance data, including domain-specific challenges. Your Responsibilities: Develop and implement AI/ML models, particularly those involving Computer … Vision (e.g., image recognition, medical imaging analysis, fraud detection, facial recognition, and automated surveillance systems). Develop and deploy AI/ML models for applications such as disease diagnosis, patient outcome prediction, fraud detection, and risk modeling. Develop expertise in Large Language Models (LLMs), Natural Language Processing (NLP), text and speech recognition systems, and cloud platforms such as Azure … Python, R, SQL, Spark, Scala. Expertise in machine learning frameworks for like TensorFlow, PyTorch, Scikit-learn, Keras, ONNX, fast.ai and other leading frameworks. Expertise in LLMs for healthcare text analysis (e.g., analyzing medical records or patient notes). Proficiency in NLP techniques such as sentiment analysis, named entity recognition, and text summarization. Knowledge of deep learning More ❯

as Git. Required skills Experience in retraining LLMs on various datasets Conversational AI Python Docker Preferred Skills: Experience with specialized AI domains such as conversational AI, sentiment analysis, or recommendation systems. Knowledge of model interpretability techniques and responsible AI practices. Familiarity with MLOps pipelines for continuous integration and deployment of AI models. Experience with API development and More ❯

Contribute to the development of scalable algorithms for processing large datasets, implement and evaluate machine learning and deep learning algorithms for tasks such as text classification, sentiment analysis, entity recognition, and summarization. Assist in the design, development, and testing of ML models for real-time processing of unstructured data. Collaborate with senior team members to analyze the … of data structures and algorithms. Proficient in Machine Learning, including understanding Neural Networks and foundational concepts of NLP tasks such as Tokenization, Named Entity Recognition (NER), Sentiment Analysis, Part-of-Speech (POS) Analysis. Experience or coursework in Deep Learning frameworks like TensorFlow or PyTorch. Strong problem-solving skills and a curiosity for learning new technologies. Good verbal More ❯

environment, for everyone. Your Skills and Experience Capabilities in a range of AI techniques (e.g. supervised and un-supervised machine learning techniques, GenAI, deep learning, graph data analytics, statistical analysis, time series, geospatial, NLP, sentiment analysis, pattern detection, etc.). Strong communication skills - able to compellingly present work to clients, disseminating complex information in an easy More ❯

enhanced or generated using AI tools. Media Relations: Build and maintain strong relationships with journalists, influencers, and media outlets, while exploring AI-based media monitoring and sentiment analysis tools to identify new opportunities for outreach and coverage. Content & Messaging: Oversee all public-facing messaging—including AI-assisted content creation for blogs, social media, executive comms, and press … releases—ensuring accuracy, tone, and strategic alignment. Brand Reputation Management: Monitor public sentiment using AI-based listening tools, manage crisis communication scenarios swiftly, and safeguard ThriveCart’s brand image. Event & Speaking Engagements: Identify and coordinate industry speaking engagements and media opportunities for ThriveCart executives, leveraging AI tools to map trends and identify strategic placements. Internal Communication: Ensure consistent More ❯

purposeful dialogue flows across chat, voice, and other channels. Apply natural language processing (NLP) and natural language understanding (NLU) techniques such as intent recognition, entity extraction, sentiment analysis, and named entity recognition to inform conversation logic. Design effective, brand-aligned prompts and interactions for large language models (LLMs), including GPT-based systems. Leverage knowledge of AI and More ❯

as TensorFlow, PyTorch, Hugging Face Transformers, or LangChain. Experience in fine-tuning, model evaluation, and prompt engineering. Strong understanding of NLP techniques including text classification, summarization, sentiment analysis, and dialogue systems. Experience building and deploying ML models in cloud environments (AWS, Azure, GCP). Clearance Applicants selected will be subject to a security investigation and may need More ❯

has been a trailblazer in its application of AI, Machine Learning (ML), and Natural Language Processing (NLP) in finance. We build models and systems that power sentiment analysis, classification, question answering, document understanding, recommendation, and more, using state of the art AI techniques including generative AI. Critical to this effort are our AI platforms, which enable teams More ❯

has been a trailblazer in its application of AI, Machine Learning (ML), and Natural Language Processing (NLP) in finance. We build models and systems that power sentiment analysis, classification, question answering, document understanding, recommendation, and more, using state of the art AI techniques including generative AI. Critical to this effort are our AI platforms, which enable teams More ❯

Key Outcomes: Retain your customers, secure their renewal and hit retention targets Amplify Customer Loyalty : Champion customer retention, ensuring seamless renewals and surpassing retention targets. Master Sentiment Analysis : Identify and neutralise potential sentiment risks across diverse stakeholders, from end users to top decision-makers, fostering enduring relationships. Empower Customer Advocacy : Lead as a vocal customer More ❯

metadata. Detail-oriented mindset, with a proactive approach to error detection and quality assurance. Familiarity with LLMs and NLP pipelines (entity linking, topic modeling, text classification, sentiment analysis, etc) Familiarity with data querying and manipulation (SQL, Python, etc) Must Have Data Annotation Data querying and manipulation Familiarity with LLMs Natural Language Processing (NLP) Ontology Development Taxonomy Management More ❯

metadata. Detail-oriented mindset, with a proactive approach to error detection and quality assurance. Familiarity with LLMs and NLP pipelines (entity linking, topic modeling, text classification, sentiment analysis, etc) Familiarity with data querying and manipulation (SQL, Python, etc) Must Have Data Annotation Data querying and manipulation Familiarity with LLMs Natural Language Processing (NLP) Ontology Development Taxonomy Management More ❯

chatbot strategy using Power Virtual Agents , ensuring seamless integration with D365 and escalation flows to human agents. Design AI for Supervisors including real-time dashboards, conversation intelligence, and sentiment analytics. Guide implementation of Intelligent IVR leveraging Azure Communication Services or integrated CCaaS platforms. Platform Integration & Governance Oversee the integration of telephony systems (e.g., Genesys, NICE, Five9, Azure Communication … integrations. Strong command of Customer Service Workspace configuration and extensibility (e.g., session templates, macros, app profiles). Expertise in AI-powered features : agent assist, conversation intelligence, call transcription, sentiment scoring. Experience with Power Platform , including Power Automate, Power Apps, and Power Virtual Agents. Solid knowledge of Azure components such as Azure Communication Services, Bot Framework, Logic Apps, Cognitive More ❯

Key Outcomes: Retain your customers, secure their renewal and hit retention targets Amplify Customer Loyalty : Champion customer retention, ensuring seamless renewals and surpassing retention targets. Master Sentiment Analysis : Identify and neutralise potential sentiment risks across diverse stakeholders, from end users to top decision-makers, fostering enduring relationships. Empower Customer Advocacy : Lead as a vocal customer More ❯

Platforms Your role will be to build extensible systems that provide compounding value over time. You'll: Build the initial sentiment and topic classification models for review analysis Develop merchant benchmarking methodology across various industry categories Create data pipelines that integrate with our existing systems Implement efficient ETL processes to ensure data quality and reliability Design the … experience in data engineering and data science roles Strong programming skills in Python and SQL Experience building NLP/ML models, particularly for text classification or sentiment analysis Background in developing data pipelines and ETL processes Proven ability to translate complex data models into business insights Experience working with large datasets (preferably e-commerce or review data … Strong communication skills to collaborate with product and design teams Nice-to-Haves Experience with e-commerce platforms, especially Shopify Background in trust metrics or customer experience analysis Knowledge of dashboard design and data visualization best practices Experience with cloud-based data infrastructure (AWS) Familiarity with modern data stack tools (Airflow, dbt, etc.) Why This Role Matters Judge.me is More ❯

environment, for everyone. Your Skills and Experience Capabilities in a range of AI techniques (e.g. supervised and un-supervised machine learning techniques, GenAI, deep learning, graph data analytics, statistical analysis, time series, geospatial, NLP, sentiment analysis, pattern detection, etc.). Strong communication skills - able to compellingly present work to clients, disseminating complex information in an easy More ❯

from Pattern matching, Chatbot implementation, and using GenAI. Proactively develop an understanding of key business problems and processes. Execute tasks throughout the model development process, including data wrangling/analysis, model training, testing, and selection. Generate structured and meaningful insights from data analysis and modelling exercises and present them in an appropriate format according to the audience. Collaborate … with other data scientists and machine learning engineers to deploy machine learning solutions. Conduct ad-hoc and periodic analysis as required by business stakeholders, the model risk function, and other groups. Required qualifications, capabilities, and skills Formal training or certification on software engineering concepts and advanced applied experience. Experience in statistical inference and experimental design (such as probability, linear … skills with Python, including libraries such as NumPy, pandas, and scikit-learn, as well as R. Understanding and usage of the OpenAI API. NLP: tokenization, embeddings, sentiment analysis, basic transformers for text-heavy datasets. Experience with LLM & Prompt Engineering, including tools like LangChain, LangGraph, and Retrieval-Augmented Generation (RAG). Experience in anomaly detection techniques, algorithms, and More ❯

with: Generative AI systems such as OpenAI, Claude, etc Prompt engineering for media intelligence, including video understanding and summarisation Cloud based audio processing systems Audio transcription, sentiment analysis, emotion evaluation Building scalable and efficient cloud-native infrastructure for processing, streaming, and analyzing audio Anomaly detection machine learning libraries Utilizing unsupervised and semi-supervised techniques to identify anomalies More ❯

NLP accuracy, Smart Response suggestions, automation rules, bot flows, and classifiers—based on customer-specific use cases. For Core: Tune AI-driven campaign tagging, content classifiers, sentiment analysis, and automated publishing logic. For Service: Optimize agent assist models, routing configurations, auto-responses, and self-service flows to improve CSAT, AHT, and containment. Workflow & KPI Rationalization Conduct workflow More ❯

Ability to work independently and as part of a team in a fast-paced environment Basic understanding of NLP concepts like intent classification, entity recognition, and sentiment analysis * Free services are subject to limitations #J-18808-Ljbffr More ❯

and GCP for deploying data science workloads. • Solid understanding of machine learning methods (supervised and unsupervised), model evaluation, and lifecycle management. • Experience with NLP tasks (e.g., sentiment analysis, entity recognition) and LLMs (e.g., GPT, Gemma). • Familiarity with LangChain (or equivalents), LLMOps, Databricks, and API management. • Understanding of TDD, modular design, authentication, version control (e.g., Git), Docker More ❯

consensus and delivering iterative development Serves as subject matter expert for products or related group of products leveraging in-depth knowledge of industry practices and trends. Conducts extensive, strategic analysis to provide consistent and competitive recommendations. Leads cross-functional sessions with teams that include Product, Technology, and other adjacent teams/functions Translates product roadmap into well-defined product … against release readiness and Go to Market standards, ensuring key aspects of the release experience including Change Checklist, Release Board, Product Pilot, Communication, Training and Colleague Sentiment Analysis are production ready Partners closely with analytics team to leverage data and colleague sentiment as a core principle, by defining product metrics, leveraging data to drive product … of complex risks, issues, and changes aligned to product management initiatives and processes, taking ownership for leadership updates and ensuring resolution/mitigation alignment with adjacent groups. Conducts research & analysis to execute against strategy, support decision making and taking accountability for driving product development ideation, and enhancements. Sharing insights with internal teams for review, validation and challenging Research demands More ❯

as Git. Required Skills: Experience in retraining LLMs on various datasets. Conversational AI. Python. Docker. Preferred Skills: Experience with specialized AI domains such as conversational AI, sentiment analysis, or recommendation systems. Knowledge of model interpretability techniques and responsible AI practices. Familiarity with MLOps pipelines for continuous integration and deployment of AI models. Experience with API development and More ❯

environment, for everyone. Your skills and experience Capabilities in a range of AI techniques (e.g. supervised and un-supervised machine learning techniques, GenAI, deep learning, graph data analytics, statistical analysis, time series, geospatial, NLP, sentiment analysis, pattern detection, etc.). Strong communication skills - able to compellingly present work to clients, disseminating complex information in an easy More ❯

environment, for everyone. Your Skills and Experience Capabilities in a range of AI techniques (e.g. supervised and un-supervised machine learning techniques, GenAI, deep learning, graph data analytics, statistical analysis, time series, geospatial, NLP, sentiment analysis, pattern detection, etc.). Strong communication skills - able to compellingly present work to clients, disseminating complex information in an easy More ❯