1 to 25 of 53 Sentiment Analysis Jobs in London

Twitter API v1.1, NLTK, Tweepy and TextBlob library and Python 3.8. Approach: My objective here is to create a PoC for “Sentiment Analysis about Climate Summit effectiveness – COP26 Summit Model” while adopting a “minimal coding with maximum efficiency” approach. We take tweets from Twitter by querying text … values. TextBlob reads each sentence and outputs sentiment score between -1 to +1 as negative to positive sentiments: Summary: Sentiment analysis about COP26 summit doesn’t end here; we have just scratched the surface from an analysis standpoint. There are various other dimensions that … communities, etc. Twitter captures tons of metadata (e.g., location, time, followers, likes, retweets, etc.) while we tweet. We can further enhance the level of analysis by adding business, political, time-series context to name a few. The main purpose is to highlight ease and speed in completing ML PoC More ❯

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 … 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 More ❯

knowledge of one or more of the following fields: Entity Recognition and Disambiguation Concept/Topic Extraction Document summarization Trend Detection Sentiment Analysis Substantial programming experience (preferably in a commercial environment) Clojure or similar languages (e.g. Java or Python) Software collaboration and revision control (e.g. Git or … AWS) Hadoop/Spark etc. Graph Databases Educational level: Master Degree Tagged as: Clustering , Data Mining , Industry , Information Retrieval , Master Degree , Sentiment Analysis , United Kingdom More ❯

frameworks. Work with cross-functional teams to implement machine learning solutions for diverse applications, including but not limited to text embeddings, sentiment analysis, question answering, summarization, and topic modeling. Utilize your expertise in semantic search, prompt engineering, and large language models (LLMs) to create robust NLP systems. … of SQL and database management. NLP Competencies : Strong understanding of NLP techniques like text embeddings, named entity recognition, machine translation, summarization, sentiment analysis, and more. Hands-on experience with pre-trained LLMs such as BERT and GPT, and advanced NLP techniques like semantic search, RAG, and agent More ❯

are not expected to be experienced in all areas listed below. AI techniques (supervised and unsupervised machine learning, deep learning, graph data analytics, statistical analysis, time series, geospatial analysis, NLP, sentiment analysis, pattern detection, etc.) Python, R, or Spark for data insights Data Bricks/ More ❯

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 More ❯

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 More ❯

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 More ❯

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 More ❯

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. More ❯

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. More ❯

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 … 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 … 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 More ❯

accuracy and performance. Apply statistical techniques to analyse data and uncover patterns. Implement validation and monitoring strategies to maintain model accuracy over time. Data Analysis & Insights Analyse large and complex datasets to extract actionable insights that drive business value. Work closely with data engineers and analysts to prepare and … transform data for model development. Generate insights from data using Exploratory Data Analysis (EDA) and model interpretability tools such as SHAP and LIME. Undertake preprocessing of structured and unstructured data, including text processing and cleaning for NLP applications. Strategic Collaboration & Product Development Work with product managers and stakeholders to … related field. Experience in productionizing machine learning models and working with APIs for data extraction. Experience with NLP including Text Classification, Sentiment Analysis, and Topic Modelling using tools like NLTK, BERT, and GCP NLP API. Fluent in English, both verbal and written What We Offer Competitive base More ❯

ability to effectively collaborate with cross-functional teams Strong problem-solving and decision-making abilities Knowledge of agile project management methodologies Experience with data analysis and reporting Ability to adapt to changing priorities and work well under pressure Project management certification (e.g., PMP) is a plus Bachelor's degree … Chatbots and Virtual Assistants : Deploy AI-driven chatbots to handle routine inquiries, provide 24/7 support, and reduce wait times. Sentiment Analysis : Use AI to analyze customer feedback and sentiment from various channels to improve services. 2. Fraud Detection and Prevention Real-Time Monitoring More ❯

Your Skills and Experience Proficiency in AI techniques such as supervised and unsupervised machine learning, GenAI, deep learning, graph analytics, NLP, sentiment analysis, etc. Excellent communication skills to present complex work clearly to clients and manage stakeholder relationships. Experience winning work with private and public sector clients More ❯

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 More ❯

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 More ❯

decisions. Specific AI experience: Expertise in designing systems that process and interpret data, enabling products such as: Assistants or co-pilots Sentiment analysis tools for customer feedback Chatbots and conversational interfaces Summaries of complex data to support users to make decisions or take action Diagnostics Personalization or … Predictive analytics Data visualizations incorporating AI insights Anomaly detection Experience in designing for comprehension, and trust in the results of the AI summary or analysis Collaboration with AI Engineers and Data Scientists: Bridging the gap between design and technical teams by translating abstract AI concepts into functional, user-friendly More ❯

building tools that don’t just react to markets - they anticipate them. Our flagship product, Trading Co-Pilot, delivers real-time sentiment analysis, predictive forecasts, and narrative detection that help our clients stay ahead of market-moving events. With a team of world-class engineers, data scientists More ❯

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 … 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 More ❯

Lead CRM Implementation & Integration: Develop and execute CRM strategies focused on developer needs; ensure data quality; create a unified reporting framework. Oversee Data Collection & Analysis Projects: Manage social listening and research projects; translate data into insights supporting growth and governance monitoring; maintain early warning systems. Develop Innovative Research Methodologies … AI for Data Insights: Use AI and machine learning tools to optimize data collection, insights, and predictive accuracy; incorporate trend prediction, sentiment analysis, and community modeling. Link Data to Business Objectives: Establish metrics linking ecosystem data to IO's strategic goals, demonstrating contributions of community initiatives. Promote More ❯

domain. Hands-on experience with natural language processing (NLP) models. Practical use of large language models (LLMs) for tasks like text generation and sentiment analysis. Experience with fine-tuning LLMs using techniques such as LoRA or qLoRA. Familiarity with performance optimization tools like DeepSpeed for accelerated model training. More ❯

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 More ❯

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 More ❯

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 More ❯