6 Textblob Jobs

Job Type Full-time Description Why Birdeye? Birdeye is the highest-rated reputation, social media, and customer experience platform for local businesses and brands. Over 150,000 businesses use Birdeye’s AI-powered platform to effortlessly manage online reputation, connect with prospects through social media and digital channels, and gain customer experience insights to grow sales and thrive. At Birdeye, innovation isn't just a goal – it's our driving force. Our commitment to pushing boundaries and redefining industry standards has earned us accolades as one of the foremost providers of AI, Reputation Management, Social Media, and Customer Experience software by G2. Founded in 2012 and headquartered in Palo Alto, Birdeye is led by a team of industry experts and innovators from Google, Amazon, Salesforce, and Yahoo. Birdeye is backed by the who’s who of Silicon Valley - Salesforce founder Marc Benioff, Yahoo co-founder Jerry Yang, Trinity Ventures, World Innovation Lab, and Accel-KKR. Role Description: This is a full-time remote role for a Data Scientist at Bideye. Primary Skills: Data Science, AI/ML, GenAI, LLM, NLP, Any Cloud (Azure/AWS/GCP) Roles & Responsibilities: Develop custom data models and algorithms to apply to data sets. Developing and implementing advanced machine learning models to address complex problems. Clearly communicate findings and recommendations, data-driven insights to PMs and executives. Requirements Bachelors/Masters degree in Computer Science, Engineering, or a related technical field with minimum 1-2 years' experience. Experience in performing prompt engineering and fine-tuning of the AI/ML, GenAI, LLM models. Experience in NLP tools such as Word2Vec, TextBlob, NLTK, SpaCy, Gensim, CoreNLP, BERT, GloVe etc. Experience in AWS / Azure / GCP cloud and deploying the APIs using the latest frameworks like FastAPI/ gRPC etc. Experience in Docker for deploying the containers. Experience in NoSQL/SQL databases. Good programming skills in Python. Domain knowledge in Online Reputation management or experience in a product-based company (added advantage). Expertise in delivering end-to-end analytical solutions covering multiple technologies & tools to multiple business problems. Why You’ll Join Us At Birdeye, we are relentless innovators driven by a singular goal: to lead our category with unparalleled excellence. We don't just set goals – we surpass them. We're a team of doers who roll up our sleeves and get the job done, delivering on our promises with unwavering dedication. Working here means embracing a culture of action and accountability, where every person is empowered to make an impact. We don't just talk about making a difference – we make it happen. Show more Show less

About Us Jar is India’s leading Daily Saving app that helps people build strong saving habits—one small step at a time. Our goal is to make saving simple, rewarding, and truly life-changing . Founded in 2021 by Misbah Ashraf and Nishchay AG , Jar is a Bengaluru-based startup with one simple belief: saving a little every day in 24K Digital Gold can truly transform your future. Today, 20 million+ Indians trust Jar as their saving partner. With flexible saving options— Daily, Weekly, Monthly, and Instant Saving —we have made it easy for everyone to save in their own way and withdraw anytime. We are one of the leaders in UPI autopay transactions, crossing more than 1 million transactions per day. In 2023, we expanded our vision with Nek , our jewelry brand crafted to bring together luxury and affordability, it has since surpassed ₹100 crore in revenue. We have a big dream of bringing “ Har Ghar Sona”. Small, consistent savings are just the start. We’re here to walk alongside our users, helping Indians secure their financial future every step of the way. Backed by Tiger Global Management, Arkam Ventures, and WEH Ventures, among others, we have raised 50 million+ in funding. In January 2025 , we hit a huge milestone of becoming profitable . Now, we’re charging ahead, focused on sustainable growth and scaling impact. And this is just the beginning! What will be your responsibilities? Data Analysis & Insights Perform deep dives on large, structured, and unstructured datasets to identify trends, irregularities, and actionable insights that drive product development and business decisions. Provide actionable insights Develop and maintain dashboards and reports for key stakeholders. Continuously monitor transactions to ensure accuracy, completeness, and integrity. Ensure data accuracy and consistency across multiple sources. Identify discrepancies, gaps, and failures in transactions and escalate for immediate resolution. Analyze historical sales data and market trends to develop accurate demand forecasts. Strategic Decision-Making Collaborate with product, engineering, and business teams to solve problems using data. Lead analysis to improve key retention and renewal metrics such as churn rate, renewal rate, transaction success rate, and GMV growth Support A/B testing and experiments to optimize product and feature performance. Analyze transaction failures, payment declines, and retry success rates to optimize the auto debit payment funnel. Data Management & Modeling Design and optimize data models that support real-time transaction monitoring, churn prediction, and cohort analysis for subscription-based customers. Partner with data engineers to ensure data accuracy, to improve data collection, completeness, and accessibility. Build and optimize reports that track business performance over time. Automate recurring reports and processes to improve efficiency. Leadership & Mentorship Guide and mentor junior analysts in best practices, technical skills, and storytelling through data. Lead projects end-to-end, ensuring clarity, timeliness, and high-quality outcomes. Metrics & Reporting & Ownerships Own reporting of subscription transactions, payment success rates, churn trends, and GMV impact, ensuring timely insights to Business & Product teams. Automate and optimize reporting to provide timely insights to leadership. Supporting other teams in setting up success metrics for particular products/features What’s required from you? Technical Skills Strong proficiency in Python & MongoDb for data analysis, including Pandas, NumPy, Scikit-learn, Matplotlib/Seaborn, Dask, Stats models, Re(regular expressions for text cleaning), textblob (sentiment analysis & text processing) & Automations. Object oriented programming is a plus. SQL: Expertise in writing complex SQL (postgres) queries for data extraction, transformation, and reporting. Process, clean, and wrangle large datasets using Python to ensure data quality and readiness for analysis. Strong understanding of Excel/Google Sheets for quick ad-hoc analysis. Experience working with large, structured/unstructured datasets. Able to develop KPIs related to retention, acquisition, A/B experiments. Visualization Tools: Data Exploration and Visualization with tools like Amplitude, Clevertap, MS Excel, Tableau, Power BI, etc. Soft Skills High sense of ownership, accountability, and proactive problem-solving mindset. Strong problem-solving, critical thinking, and business acumen. Excellent communication skills with the ability to translate complex findings into clear insights for non-technical stakeholders. Experience 3+ years of experience in data analysis, preferably in fintech or startups. Proven experience leading high-impact projects independently. A desire to work in a fast-paced environment What makes us different? We’re not just building a product—we’re shaping the future of savings in India. We seek people who bring passion, energy, and fresh ideas to help us make that happen. Experience matters, but we are a potential first organisation. We move fast, learn from our mistakes, and take bold risks to solve problems that haven’t been attempted before. If you’re excited about working in an environment where people inspire and truly support each other, you’ve found the right fit. What do we stand for? The Five Values That We Live By Passion: At Jar, we strive to create an environment where people love what they do, are motivated and equipped to do their best work. Equality: We bring diverse skills, ideas, and experiences to the table, supporting and challenging each other across teams to create something bigger than ourselves. Growth: When our people grow, Jar grows. We create opportunities for learning, development, and meaningful impact. Accountability: The core of our work ethic is taking ownership of our work, showing initiative, and having the freedom to ask questions. Consistency: We believe in doing the right things consistently. Big change doesn’t happen overnight—it’s built one step at a time. Join us and let’s build something amazing together! What employee benefits do we have? Glad you asked! Among other things, we have Medical Insurance for employees and their families ESOPs allocation Pluxee meal card Swish club card for exclusive employee discounts Advance salary plans Relocation assistance L&D programmes Skills: python,tableau,sql,numpy,data wrangling,data exploration,scikit-learn,power bi,mentoring,clevertap,report writing,analytical skills,nlp,pandas,mongodb,excel,matplotlib,data analysis,business sense,amplitude,ms excel,google sheets,data visualization,querying,etl,data analysis packages Show more Show less

Lead Data Scientist Title: Lead Data Scientist Role Description: This is a full-time remote role for a Lead Data Scientist at Birdeye. Primary Skills: Data Science, AI/ML, GenAI, LLM, NLP, Any Cloud (Azure/AWS/GCP), MLOps Roles & Responsibilities: Develop custom data models and algorithms to apply to data sets. Developing and implementing advanced machine learning models to address complex problems. Clearly communicate findings and recommendations, data-driven insights to PMs and executives. Develop custom data models and algorithms to apply to data sets. Developing and implementing advanced machine learning models to address complex problems. Lead and mentor a team of data scientists, providing guidance on best practices and technical expertise. Collaborate with cross-functional teams to define data-driven strategies and integrate data science solutions into products. Continuously evaluate and improve the performance of existing models and algorithms. Stay updated with the latest advancements in AI/ML and propose innovative solutions to enhance the company's capabilities. Qualifications: Bachelors/Masters degree in Computer Science, Engineering, or a related technical field with minimum 5-8 years' experience. Minimum of 2 years of experience in leading a team of junior Data Scientist. Should have been involved in end-to-end delivery of the scalable, optimized and enterprise AI solutions. Experience in performing prompt engineering and fine-tuning of the AI/ML, GenAI, LLM models. Practical hands-on fine-tuning/transfer learning/optimization of the Transformer architecture based Deep Learning models. Experience in NLP tools such as Word2Vec, TextBlob, NLTK, SpaCy, Gensim, CoreNLP, BERT, GloVe etc. Experience in AWS / Azure / GCP cloud and deploying the APIs using the latest frameworks like FastAPI/ gRPC etc. Experience in Docker for deploying the containers. Deployment of the ML models on the Kubernetes clusters Experience in NoSQL/SQL databases. Good programming skills in Python. Domain knowledge in Online Reputation management or experience in a product-based company (added advantage). Expertise in delivering end-to-end analytical solutions covering multiple technologies & tools to multiple business problems. Understanding of big data technologies like Hadoop, Spark, and Hive. Strong knowledge of statistical methods and experimental design. Experience with MLOps practices for CI/CD in machine learning. Strong project management skills, with the ability to manage multiple projects simultaneously. Excellent communication and presentation skills, with the ability to explain complex technical concepts to non-technical stakeholders. Interested candidates, please send their resumes to iqbal.kaur@birdeye.com Regards Iqbal kaur Show more Show less

Title: Senior Data Scientist (NLP) Primary Skills: Data Science, AI/ML, GenAI, LLM, NLP, Any Cloud (Azure/AWS/GCP) Roles & Responsibilities: Develop custom data models and algorithms to apply to data sets. Developing and implementing advanced machine learning models to address complex problems. Clearly communicate findings and recommendations, data-driven insights to PMs and executives. Qualifications: Bachelors/Masters degree in Computer Science, Engineering, or a related technical field with minimum 5 years' experience. Experience in performing prompt engineering and fine-tuning of the AI/ML, GenAI, LLM models. Practical hands-on fine-tuning/transfer learning/optimization of the Transformer architecture-based Deep Learning models. Experience in NLP tools such as Word2Vec, TextBlob, NLTK, SpaCy, Gensim, CoreNLP, BERT, GloVe etc. Experience in AWS / Azure / GCP cloud and deploying the APIs using the latest frameworks like FastAPI/ gRPC etc. Experience in Docker for deploying the containers. Deployment of the ML models on the Kubernetes clusters Experience in NoSQL/SQL databases. Good programming skills in Python. Domain knowledge in Online Reputation management or experience in a product-based company (added advantage). Expertise in delivering end-to-end analytical solutions covering multiple technologies & tools to multiple business problems. Interested candidates, please send their resumes to iqbal.kaur@birdeye.com Regards Iqbal kaur Show more Show less

Overview: We are seeking an exceptional and technically accomplished Senior Data Scientist to join our rapidly growing team. This role is ideal for a hands-on AI expert with deep experience in Large Language Models (LLMs) , Natural Language Processing (NLP) , Cognitive AI , Conversational AI , and Agentic AI systems . You will work on designing, developing, and scaling state-of-the-art AI solutions that drive business innovation, operational intelligence, and customer experience transformation. This is a high-impact individual contributor role, focused on technical excellence and product-grade AI development. Key Responsibilities LLM & Cognitive AI Solution Development Architect and fine-tune LLM-based solutions (e.g., GPT, LLaMA, Claude, Mistral) using transfer learning, PEFT, and retrieval-augmented generation (RAG). Develop Agentic AI architectures with autonomous behavior and multi-agent collaboration capabilities. Apply prompt engineering , in-context learning , and tool former-style techniques to enable complex reasoning and task execution. Build Conversational AI systems using Transformer-based backbones and orchestration tools (LangChain, Haystack, Rasa, Semantic Kernel). Natural Language Processing (NLP) Design and implement advanced NLP pipelines for semantic search, summarization, NER, text classification, and knowledge extraction. Utilize and integrate tools such as SpaCy , BERT , RoBERTa , GloVe , Word2Vec , NLTK , and TextBlob . Conduct advanced text preprocessing, dependency parsing, sentiment analysis, tokenization, and multilingual NLP modeling. AI/ML Engineering Build scalable ML pipelines with FastAPI, gRPC, and RESTful interfaces. Containerize services using Docker and deploy to production environments via Kubernetes and cloud-native workflows. Integrate models into real-time and batch data systems, optimizing for latency, throughput, and reliability. Cloud & Infrastructure Develop and deploy solutions on AWS , Azure , or Google Cloud Platform (GCP) . Leverage services like SageMaker, Vertex AI, Azure ML Studio, and serverless orchestration tools. MLOps & CI/CD Design and maintain end-to-end MLOps pipelines using tools like MLflow, Kubeflow, or TFX for reproducibility and traceability. Automate model testing, monitoring, versioning, and rollback strategies in production. Big Data & Analytics Apply Spark, Hadoop, and Hive to process large-scale datasets efficiently. Perform complex data transformations and statistical modeling to extract actionable insights. Database & Data Engineering Interface with SQL and NoSQL systems (PostgreSQL, MongoDB, DynamoDB, etc.) for efficient data retrieval and processing. Design data schemas and optimize query performance for AI-centric applications. Cross-functional Collaboration Work closely with product managers, engineers, and domain experts to identify high-impact problems and deliver AI-driven solutions. Communicate findings and solution architectures clearly to technical and non-technical stakeholders. Technical Skills Expert in Python , PyTorch, HuggingFace Transformers, LangChain, and OpenAI/Anthropic/LLama APIs. Deep understanding of Transformer architectures , Attention Mechanisms , and LLM fine-tuning techniques . Familiarity with Agentic AI paradigms , including memory management, autonomous goal completion, and tool use. Strong experience with cloud platforms, container orchestration (Docker + Kubernetes), and deployment automation. Proficient in statistical modeling, probabilistic reasoning, and experimental design. Bonus Experience in Online Reputation Management (ORM) or product-centric platforms . Publications or open-source contributions in AI/ML/NLP.

Role Overview: We' re looking for a Lead Data Scientist to join our fast-growing, mission-driven team. This is a high-impact leadership role at the intersection of technology, strategy, and innovation where your expertise will power intelligent solutions that redefine how we think about data, products, and customer experience. If you thrive in high-performance environments and want to lead cutting-edge projects with Generative AI, LLMs, and large-scale NLP systems, this is your opportunity to make a lasting impact. Key Responsibilities: Build the Future with AI/ML Architect scalable AI systems to solve real-world, high-value business challenges cross domains. Design and deploy cutting-edge solutions with Generative AI, Transformer architectures, and custom Large Language Models (LLMs). Apply state-of-the-art ML techniques prompt engineering, transfer learning, multi-modal learning to push the boundaries of what's possible. NLP at Scale Lead the development of advanced NLP systems: semantic search, question answering, summarization, classification, and conversational AI. Work with best-in-class models and libraries: BERT, GPT, RoBERTa, Word2Vec, SpaCy, NLTK, Hugging Face Transformers, and more. Leverage language understanding to transform unstructured data into strategic insights. Full-Lifecycle Model Deployment Build robust MLOps pipelines for training, testing, deployment, and monitoring using MLflow, Kubeflow, Airflow, and CI/CD tools. Containerize and orchestrate AI models using Docker and Kubernetes across cloud environments (AWS, GCP, Azure). Design APIs and inference services using FastAPI or gRPC, optimized for performance, scalability, and uptime. Lead, Inspire, and Elevate Build and mentor a world-class data science team, nurturing talent and fostering a culture of curiosity, experimentation, and technical excellence. Drive the data science strategy, influence key decisions, and align AI initiatives with business goals. Establish best-in-class practices for model development, code quality, documentation, and performance evaluation. Data at the Core Work hands-on with structured, semi-structured, and unstructured data. Optimize high-volume data pipelines, integrate with SQL and NoSQL databases, and leverage big data ecosystems like Spark, Hive, and Hadoop. Use statistical modeling and experimental design to derive actionable intelligence from data Collaborate Across the Enterprise Work closely with engineering, product, and executive teams to define problems, explore solutions, and deliver AI products that move the needle. Translate technical concepts into strategic recommendations and insights that influence roadmaps and revenue. Champion AI literacy and advocate for ethical, explainable, and scalable data science across the organization. Education Bachelors or Master’s in Computer Science, AI, Data Science, Machine Learning, Engineering, or a related technical discipline. PhD is a plus. Experience 6+ years of experience in data science or machine learning, with 2+ years in a leadership or managerial role. Proven record of building and deploying AI solutions at scale in real-world production environments. Experience in GenAI, NLP, cloud-native architectures, and full-cycle ML development. Technical Expertise Languages & Libraries: Python, Scikit-learn, PyTorch, TensorFlow, Hugging Face, NumPy, Pandas NLP: BERT, GPT, Word2Vec, SpaCy, NLTK, TextBlob, CoreNLP, Transformer-based architectures Cloud & Deployment: AWS, Azure, GCP, Docker, Kubernetes, FastAPI, gRPC Big Data: Spark, Hive, Hadoop, Kafka Data Systems: PostgreSQL, MongoDB, Cassandra, Snowflake, BigQuery MLOps & Monitoring: MLflow, Airflow, Kubeflow, Prometheus, Grafana Nice to Have Experience in online reputation management, customer analytics, or product-led organizations. Familiarity with responsible AI, fairness, and explainability techniques (SHAP, LIME).