136 Data Scientist Jobs

Responsibilities : Data Analysis and Exploration : - Analyze large datasets to identify trends, patterns, and insights. - Perform exploratory data analysis (EDA) to understand data characteristics and relationships. - Develop and implement data preprocessing and cleaning techniques. Machine Learning Model Development : - Design, develop, and evaluate machine learning models for various applications (prediction, classification, clustering). - Select and implement appropriate algorithms and techniques based on project requirements. - Optimize model performance and ensure scalability. Statistical Analysis : - Apply statistical methods to analyze data and draw meaningful conclusions. - Conduct hypothesis testing and statistical modeling. - Develop and interpret statistical reports and visualizations. Data Visualization and Communication : - Create compelling visualizations to communicate data insights to technical and non-technical audiences. - Develop dashboards and reports to monitor key performance indicators (KPIs). - Present findings and recommendations to stakeholders. Collaboration and Communication : - Collaborate with engineers, product managers, and other stakeholders to define project requirements and deliver solutions. - Communicate complex technical concepts clearly and effectively. - Contribute to the development of data science best practices. Model Deployment and Monitoring : - Deploy machine learning models into production environments. - Monitor model performance and retrain models as needed. Qualifications : - Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or a related field. - 2-6 years of experience in data science. - Strong proficiency in Python and relevant libraries (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch). - Experience with SQL and database management. - Solid understanding of machine learning algorithms and statistical methods. - Experience with data visualization tools (Tableau, Power BI, Matplotlib, Seaborn). - Excellent problem-solving and analytical skills. - Strong communication and collaboration skills. - Experience with cloud platforms (AWS, Azure, GCP) is a plus.

#GenerativeAI Experts ready for AI race, this is for you! Announcing Hexaware conducting Walkin Drive for AI Engineer and Lead Data Scientist (GenAI)-Pune Location-12th July 2025(Saturday) Interested candidates share your CV at umaparvathyc@hexaware.com Open Positions: AI Engineer/Lead Data Scientist (GenAI) AI Engineer Experience- 3+years Lead Data Scientist (GenAI) Experience- 7+years Notice Period- 15 days/30days Max (who serving Notice Period) Walkin Drive Location- Pune Date of drive- 12th July 2025(Saturday) Must have Experience: LLM, Advance RAG, NLP, transformer model, LangChain Technical Skill: 1. Strong Experience in Data Scientist (GENAI) 2. Proficiency with Generative AI models like GANs, VAEs, and transformers 3. Expertise with cloud platforms (AWS, Azure, Google Cloud) for deploying AI models 4. Strong Python Fast API experience, SDA based implementations for all the APIs 5. Knowledge of Agentic AI concepts and applications

Role : AI Research Engineer - AI Pair Programming About Us : We are developing a cutting-edge AI pair programming extension for VS Code, aimed at revolutionising the way developers write code. Our mission is to enhance developer productivity and code quality through advanced AI assistance. We're seeking an experienced AI Research Engineer to join our innovative team at PureCode AI and help push the boundaries of AI in software development. Position Overview : We are looking for an AI Research Engineer with a strong background in Large Language Models (LLMs) and their applications in code generation and understanding. The ideal candidate will contribute to our research efforts in contextual retrievals, rerankers, and vector databases, with a focus on optimising developer workflows. Key Responsibilities : - Conduct advanced research in AI and machine learning, specifically focusing on LLMs for code generation and comprehension - Implement or optimise state-of-the-art AI models to enhance our AI pair programming capabilities - Develop and refine algorithms for contextual code retrieval, reranking, and efficient use of vector databases - Collaborate with the development team to integrate research findings into our VS Code extension - Contribute to the improvement of developer workflow optimisation through AI-assisted coding - Evaluate and fine-tune models to ensure high-quality code suggestions and analysis - Stay abreast of the latest advancements in AI research and propose innovative applications for our product Qualifications : - Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a related field - Minimum of 3 years of experience in AI engineering and research, with a focus on NLP and LLMs - Strong background in machine learning, deep learning, and natural language processing - Expertise in implementing and deploying AI models for code analysis and generation - Experience with contextual retrieval systems, rerankers, and vector databases - Proficiency in Python and familiarity with machine learning frameworks such as PyTorch or TensorFlow - Solid understanding of API development practices and tools, particularly in the context of Generative AI. - Familiarity with VS Code extension development is a plus Required Skills : - Strong problem-solving skills and ability to translate research into practical applications - Excellent programming skills and ability to write clean, efficient code - Good understanding of software engineering principles and best practices - Ability to work effectively in a collaborative team environment - Strong communication skills to explain complex AI concepts to both technical and non-technical stakeholders - Self-motivated with the ability to work independently on research projects Preferred Experience : - Previous work on AI-assisted coding tools or IDE plugins - Contributions to open-source AI or developer tool projects - Experience with large-scale machine learning model deployment and optimisation - Familiarity with MLOps practices and tools What We Offer : - Opportunity to work on cutting-edge AI technology that directly impacts developers worldwide - Collaborative and innovative work environment - Competitive salary and benefits package - Professional development opportunities and support for attending relevant conferences - Chance to publish and present research findings in academic and industry forums Location- Delhi NCR, Bangalore, Chennai, Pune, Kolkata, Ahmedabad, Mumbai, Hyderabad

Job Position : Principal Data Scientist / Sr Data Scientists /Data Scientist / Jr. Data Scientist / Data Science Intern / Machine Learning Engineer-Global Tech AI Health Startup. Joining : Immediately. Job Location : Delhi NCR, India. Global HQ, Benovymed Global Technology Development and Innovation Center & Benovymed Global R and D, and AI Health Innovation Center in Delhi NCR. Job Role Responsibility Description : We are looking for passionate, Strong experience with an entrepreneur mindset to join us as Hardcore Full Stack Data Scientist end-to-end single-handed multi-hat role who is already working in applied AI in ML, deep Learning, ANN, and CNN platform specifically working as single-handed doers or in a small Data Science Team with full end to end ownership of Data Science work commitment delivery as Data Scientist working in any reputed AI Data Science is driven Tech startup preferably in Healthcare. Required Skillsets : - Needs to have statistical, mathematical, and predictive modeling as well as business strategy skills to build the algorithms necessary to ask the right questions and find the right answers. - Need to be able to communicate their findings, orally and visually. - Need to understand how the products are developed and even more important, as big data touches the privacy of consumers, they need to have a set of ethical responsibilities.- - Need to have a natural desire to go beneath the surface of a problem. - Confident and self-secure as they more often than not will have to deal with situations where there is a lot of unknown. - Good knowledge & experience in Artificial Neural Network ( ANN ), AI conversational Chatbot & Needs to be able to write the required Algorithm and coding programming. - Preferably in different programming languages such as Python, Tensor Flow, Keras, AWS (ML and DL), Numpy, and Pytorch. In addition the need to be familiar with disciplines as follows : - Natural Language Processing, Machine learning, Conceptual modeling, Statistical analysis, Predictive Modeling, and Hypothesis testing. Data scientists should have at least some of the following capabilities : - Cleaning data, formatting data, Having the ability to query databases & perform statistical analysis, building AI Data Modelling, validating the AI Model, and deployment. - Being able to develop or program databases. - Having a good understanding of design & architecture principles. Qualification : B.Tech / M.Tech in CSE / Electrical / Electronics & Communication/ Maths & Computing /Statistics /BioTech/BioStat / Clinical Engineering in Data Science / Machine Learning from Top-rated Tech University / Top rated IIT /IIIT. Mandatory Requirement : Experience : - Post last qualification of at least 0 to 7 Years of strong experience exclusive in real Industry Projects in applied AI ML & Deep Learning Data Science in an early-stage AI Health startup at the role and designation as a single-handed full-stack Principal Data Scientist / Sr. Data Scientist. - Hardcore in ANN /Deep Learning /Machine Learning/NLP with at least 2-20 good Applied AI-oriented Applied Research Projects & applications with hardcore experience working on ANN, CNN, RNN, and deep learning in Digital Health startups to solve specific complex problems. CTC : - Best Package in Industry. - Terms & Conditions Apply as per our organization. - To deserving eligible candidates only, the company Equity / ESOP may be given also as a part of a Package for a long-term career opportunity. - Apply with your CV with passport size photo, & current CTC, expected CTC, Notice Period, Project details & cover letter.

Employment Type : Full Time, Permanent Working mode : Regular Notice Period : Immediate - 15 Days About the Role : We are seeking a highly skilled Senior Data Scientist to join our team and contribute to cutting-edge projects. As a key member of our data science team, you will leverage your expertise in machine learning, natural language processing, and data engineering to develop innovative solutions that drive business value. Responsibilities : - Machine Learning Model Development : Design, develop, and deploy advanced machine learning models, focusing on natural language processing tasks such as text classification, sentiment analysis, and language generation. - Data Engineering : Extract, transform, and load (ETL) data from various sources, ensuring data quality and consistency. - NLP Techniques : Apply state-of-the-art NLP techniques, including language models and text processing, to solve complex problems. - Python and ML Frameworks : Utilize Python programming language and popular ML frameworks like PyTorch or TensorFlow to build efficient and scalable models. - Cloud and Containerization : Leverage cloud platforms (GCP, AWS) and containerization technologies (Docker) for efficient deployment and management of ML models. - Database Management : Work with relational databases (Postgres, MySQL) to store, manage, and query large datasets. - Knowledge Graphs and ML Publications : Contribute to the development of knowledge graphs and stay updated with the latest advancements in the field through research and publications. Qualifications : Experience : 4-7 years of hands-on experience in data science, with a strong focus on machine learning and natural language processing. Technical Skills : - Proficiency in Python programming language. - Deep understanding of machine learning algorithms and techniques. - Expertise in NLP, including language models and text processing. - Familiarity with ML frameworks like PyTorch or TensorFlow. - Experience with cloud platforms (GCP, AWS) and containerization (Docker). - Knowledge of relational databases (Postgres, MySQL). Soft Skills : - Strong problem-solving and analytical skills. - Excellent communication and collaboration abilities. - Ability to work independently and as part of a team. Benefits : - Competitive salary and benefits package. - Opportunities for professional growth and development. - Collaborative and supportive work environment.

Requirement : Bachelor's Degree in Computer Science, Operations Research, Statistics, or related field. Knowledge of R, or Python Knowledge of building regression and classification models Familiarity with any or all of, Regularization methods: Lasso, Ridge Ensemble methods: Random Forest, Boosting Time Series analysis: Auto-regression, moving average, etc. Graphs modeling Support Vector Machines Decision trees Preferred : Master's or higher degrees. Industry experience in the field of Data Science. Participation in competitions like Kaggle, Netflix Data Challenge. Open source contributions in areas of Data Science (Machine Learning, Deep Learning, Statistical Learning). Worked on Scala and/or Spark. Understanding of generative AI concepts, such as transformers, diffusion models, and LLMs

Job Position : Principal Data Scientist / Sr Data Scientists /Data Scientist / Jr. Data Scientist / Data Science Intern / Machine Learning Engineer-Global Tech AI Health Startup. Joining : Immediately. Job Location : Delhi NCR, India. Global HQ, Benovymed Global Technology Development and Innovation Center & Benovymed Global R and D, and AI Health Innovation Center in Delhi NCR. Job Role Responsibility Description : We are looking for passionate, Strong experience with an entrepreneur mindset to join us as Hardcore Full Stack Data Scientist end-to-end single-handed multi-hat role who is already working in applied AI in ML, deep Learning, ANN, and CNN platform specifically working as single-handed doers or in a small Data Science Team with full end to end ownership of Data Science work commitment delivery as Data Scientist working in any reputed AI Data Science is driven Tech startup preferably in Healthcare. Required Skillsets : - Needs to have statistical, mathematical, and predictive modeling as well as business strategy skills to build the algorithms necessary to ask the right questions and find the right answers. - Need to be able to communicate their findings, orally and visually. - Need to understand how the products are developed and even more important, as big data touches the privacy of consumers, they need to have a set of ethical responsibilities.- - Need to have a natural desire to go beneath the surface of a problem. - Confident and self-secure as they more often than not will have to deal with situations where there is a lot of unknown. - Good knowledge & experience in Artificial Neural Network ( ANN ), AI conversational Chatbot & Needs to be able to write the required Algorithm and coding programming. - Preferably in different programming languages such as Python, Tensor Flow, Keras, AWS (ML and DL), Numpy, and Pytorch. In addition the need to be familiar with disciplines as follows : - Natural Language Processing, Machine learning, Conceptual modeling, Statistical analysis, Predictive Modeling, and Hypothesis testing. Data scientists should have at least some of the following capabilities : - Cleaning data, formatting data, Having the ability to query databases & perform statistical analysis, building AI Data Modelling, validating the AI Model, and deployment. - Being able to develop or program databases. - Having a good understanding of design & architecture principles. Qualification : B.Tech / M.Tech in CSE / Electrical / Electronics & Communication/ Maths & Computing /Statistics /BioTech/BioStat / Clinical Engineering in Data Science / Machine Learning from Top-rated Tech University / Top rated IIT /IIIT. Mandatory Requirement : Experience : - Post last qualification of at least 0 to 7 Years of strong experience exclusive in real Industry Projects in applied AI ML & Deep Learning Data Science in an early-stage AI Health startup at the role and designation as a single-handed full-stack Principal Data Scientist / Sr. Data Scientist. - Hardcore in ANN /Deep Learning /Machine Learning/NLP with at least 2-20 good Applied AI-oriented Applied Research Projects & applications with hardcore experience working on ANN, CNN, RNN, and deep learning in Digital Health startups to solve specific complex problems. CTC : - Best Package in Industry. - Terms & Conditions Apply as per our organization. - To deserving eligible candidates only, the company Equity / ESOP may be given also as a part of a Package for a long-term career opportunity. - Apply with your CV with passport size photo, & current CTC, expected CTC, Notice Period, Project details & cover letter.

About the job : We are looking for a highly skilled Senior AI/ML Engineer with 5+ years of experience to join our team. The ideal candidate should have extensive expertise in machine learning, deep learning, and AI model development, along with a strong background in Python, NLP, computer vision, and cloud-based AI solutions. Key Responsibilities : - Design, develop, and deploy AI/ML models for real-world applications. - Work with NLP, deep learning, and traditional ML algorithms to solve complex business problems. - Develop end-to-end ML pipelines, including data preprocessing, feature engineering, model training, and deployment. - Optimize model performance using hyperparameter tuning and model evaluation techniques. - Implement AI-driven solutions using TensorFlow, PyTorch, Scikit-learn, OpenAI APIs, Hugging Face, and similar frameworks. - Work with structured and unstructured data, performing data wrangling, transformation, and feature extraction. - Deploy models in cloud environments (AWS, Azure, or GCP) using SageMaker, Vertex AI, or Azure ML. - Collaborate with cross-functional teams to integrate AI models into production systems. - Ensure scalability, performance, and efficiency of AI/ML solutions. - Stay updated with emerging AI trends and technologies to drive innovation. Required Skills : - Strong experience in machine learning, deep learning, NLP, and AI model development. - Proficiency in Python, TensorFlow, PyTorch, Scikit-learn, and OpenAI GPT models. - Expertise in NLP techniques (Word2Vec, BERT, transformers, LLMs, text classification). - Hands-on experience with computer vision (CNNs, OpenCV, YOLO, custom object detection models). - Solid understanding of ML model deployment and MLOps (Docker, Kubernetes, CI/CD for ML models). - Experience in working with cloud platforms (AWS, Azure, GCP) for AI/ML model deployment. - Strong knowledge of SQL, NoSQL databases, and big data processing tools (PySpark, Databricks, Hadoop, Kafka, etc. -Familiarity with API development using Django, Flask, or FastAPI for AI solutions. - Strong problem-solving, analytical, and communication skills. Preferred Skills : - Experience with AI-powered chatbots and OpenAI API integration. - Exposure to LLMs (GPT, LLaMA, Falcon, etc.) for real-world applications. - Hands-on experience in generative AI models.

Notice Period: Maximum 30 days Location: Bangalore, Chennai, Kolkata, Pune, and Hyderabad Note: Candidates based in Hyderabad must attend in-person interviews for the second round. Role Summary: Generative AI Specialist Mandatory Skills: Gen AI, LLMs, ML/DL/NLP, RAG, LangChain, Mistral, LLaMA, Hugging Face, Python, TensorFlow, PyTorch, Django, Vector DBs Preferred Skills: GCP/Azure/AWS, Databricks, MLOps (e.g., Kubeflow, MLflow), Kubernetes, GitHub/Bitbucket, Azure DevOps, GPT-4 Responsibilities: Design, develop, and deploy generative AI solutions using modern ML/DL techniques. Work with large-scale datasets; handle preprocessing and model optimization. Build applications using LLMs and frameworks like LangChain, leveraging models like Mistral, LLaMA, GPT-4. Research and implement cutting-edge GenAI algorithms and architectures. Ensure Responsible AI compliance and monitor model performance post-deployment. Collaborate with cross-functional teams for solution integration and data engineering. Drive innovation by staying up to date with AI trends. Provide technical leadership, mentorship, and contribute to project governance and stakeholder communication. If you meet the requirements and are looking for a new opportunity, we'd love to hear from you! Interested candidates can send their resumes to admin@spearheadps.com OR Contact us via call/WhatsApp at 9899080360

Responsibilities : - Transform raw and unstructured data into structured, actionable formats for analysis and reporting. - Write, optimize, and maintain SQL queries and stored procedures to ensure efficient data retrieval and processing. - Design and implement complex SQL queries, including Common Table Expressions (CTEs), window functions, recursive queries, dynamic pivoting and joins, to extract actionable insights from large datasets efficiently. - Design, develop, and maintain databases and data pipelines to support analytics and reporting needs. - Perform data engineering tasks, including data ingestion, cleaning, and preprocessing. - Conduct exploratory data analysis (EDA) to uncover trends, patterns, and insights. - Develop and implement machine learning (ML) models and natural language processing (NLP) solutions to solve business challenges. - Build and monitor key performance indicators (KPIs) for dashboards and reporting tools. - Create wireframes and collaborate with stakeholders to design intuitive data visualizations and dashboards. - Ensure data integrity and perform quality checks to maintain high standards of accuracy and reliability. - Collaborate with cross-functional teams to align data initiatives with business goals. - Manage data science projects from ideation to deployment, ensuring timely delivery and measurable impact. - Communicate findings and insights effectively through presentations and reports to technical and non-technical audiences/ stakeholders. - Utilize statistical modelling and data mining techniques to drive decision-making and strategy. Must-Have Skills : - Proficiency in SQL and Python/R for data manipulation and analysis. - Experience with Machine Learning (ML) and NLP techniques. - Strong understanding of EDA and statistical modelling. - Hands-on experience with Google Cloud Platform (GCP) and Vertex AI. - Excellent communication and presentation skills. - Solid grasp of data engineering principles, including ETL processes. Good-to-Have Skills : - Knowledge of data mining techniques. - Knowledge of generative AI tools and frameworks for tasks such as synthetic data generation and data augmentation. - Familiarity with dashboard wireframe creation tools and methods. - Ability to build or derive KPIs for visualization dashboards. - Expertise in Excel for advanced calculations and analysis. - Background in project management, including Agile or similar methodologies. - Experience in cross-functional team collaboration. - Hands-on experience fine-tuning or deploying pre-trained Gen AI models (e.g., Hugging Face Transformers, OpenAI APIs)

Work Location : Hyderabad/ Bangalore Working Hours : 2PM to 11PM IST Mid-Level ML Engineers / Data Scientist Role : (4-5 years of experience ) - Experience processing, filtering, and presenting large quantities (100K to Millions of rows) of data using Pandas and PySpark - Experience with statistical analysis, data modeling, machine learning, optimizations, regression modeling and forecasting, time series analysis, data mining, and demand modeling. - Experience applying various machine learning techniques and understanding the key parameters that affect their performance. - Experience with Predictive analytics (e.g., forecasting, time-series, neural networks) and Prescriptive analytics (e.g., stochastic optimization, bandits, reinforcement learning). - Experience with Python and Python packages like NumPy, Pandas and deep learning frameworks like TensorFlow, Pytorch and Keras - Experience in Big Data ecosystem with frameworks like Spark, PySpark , Unstructured DBs like Elasticsearch and MongoDB - Proficiency with TABLEAU or other web-based interfaces to create graphic-rich customizable plots, charts data maps etc. - Able to write SQL scripts for analysis and reporting (Redshift, SQL, MySQL). - Previous experience in ML, data scientist or optimization engineer role with a large technology company. - Experience in an operational environment developing, fast-prototyping, piloting, and launching analytic products. - Ability to develop experimental and analytic plans for data modeling processes, use of strong baselines, ability to accurately determine cause and effect relations. - Experience in creating data driven visualizations to describe an end-to-end system. - Excellent written and verbal communication skills. The role requires effective communication with colleagues from computer science, operations research, and business backgrounds. - Bachelors or Masters in Artificial Intelligence, Computer Science, Statistics, Applied Math, or a related field.

Job Title : AI Engineer - Azure AI. Key Responsibilities : We are seeking a highly skilled and motivated AI Engineer to join our team. In this role, you will leverage your expertise in AI technologies and the Microsoft ecosystem to design, build, and deploy intelligent agents and automation solutions that enhance business processes and deliver value to our clients. Candidates must have extensive experience in the Microsoft environment. You will collaborate with cross-functional teams to create innovative solutions using Microsoft tools and platforms. Responsibilities : Agent Development : - Design, implement, and optimize AI agents using Microsoft Azure Framework and related technologies. - Develop custom AI solutions leveraging Power Automate, Azure OpenAI, and other Microsoft tools. Solution Integration : - Deploy AI solutions within client environments, ensuring scalability and seamless integration with existing systems. - Work with stakeholders to identify automation opportunities and tailor solutions to business needs. AI Algorithm and Model Implementation : - Design and implement machine learning algorithms, focusing on natural language processing (NLP) and conversational AI. - Perform data preprocessing, feature engineering, and model training to create high-performing solutions. Collaboration and Support : - Collaborate with cross-functional teams, including software engineers, data scientists, and product managers, to deliver integrated solutions. - Provide technical guidance and support to ensure the successful adoption and use of AI-driven tools. Continuous Improvement : - Stay updated on advancements in AI, machine learning, and Microsofts AI technologies. - Contribute to knowledge sharing by conducting training sessions and documenting best practices. Preferred Skills : - Strong knowledge of Azure OpenAI, Azure AI Search Index and open source libraries such as LangChain and LlamaIndex. - Proficiency in Python and its AI/ML libraries (e.g., TensorFlow, PyTorch, scikit-learn). - Familiarity with building and managing cloud-based solutions, preferably on Microsoft Azure. - Understanding of conversational AI technologies and chatbot frameworks. - Experience with data analysis tools and techniques to uncover insights and optimize models. Requirements : - Bachelors or Masters degree in Computer Science, Data Science, or a related field. - Proven experience in developing and deploying AI/ML models in real-world applications. - Strong programming skills, especially in Python, and familiarity with version control systems like Git. - Extensive experience in the Microsoft environment and related technologies.

About the job : We are looking for a highly skilled Senior AI/ML Engineer with 5+ years of experience to join our team. The ideal candidate should have extensive expertise in machine learning, deep learning, and AI model development, along with a strong background in Python, NLP, computer vision, and cloud-based AI solutions. Key Responsibilities : - Design, develop, and deploy AI/ML models for real-world applications. - Work with NLP, deep learning, and traditional ML algorithms to solve complex business problems. - Develop end-to-end ML pipelines, including data preprocessing, feature engineering, model training, and deployment. - Optimize model performance using hyperparameter tuning and model evaluation techniques. - Implement AI-driven solutions using TensorFlow, PyTorch, Scikit-learn, OpenAI APIs, Hugging Face, and similar frameworks. - Work with structured and unstructured data, performing data wrangling, transformation, and feature extraction. - Deploy models in cloud environments (AWS, Azure, or GCP) using SageMaker, Vertex AI, or Azure ML. - Collaborate with cross-functional teams to integrate AI models into production systems. - Ensure scalability, performance, and efficiency of AI/ML solutions. - Stay updated with emerging AI trends and technologies to drive innovation. Required Skills : - Strong experience in machine learning, deep learning, NLP, and AI model development. - Proficiency in Python, TensorFlow, PyTorch, Scikit-learn, and OpenAI GPT models. - Expertise in NLP techniques (Word2Vec, BERT, transformers, LLMs, text classification). - Hands-on experience with computer vision (CNNs, OpenCV, YOLO, custom object detection models). - Solid understanding of ML model deployment and MLOps (Docker, Kubernetes, CI/CD for ML models). - Experience in working with cloud platforms (AWS, Azure, GCP) for AI/ML model deployment. - Strong knowledge of SQL, NoSQL databases, and big data processing tools (PySpark, Databricks, Hadoop, Kafka, etc. -Familiarity with API development using Django, Flask, or FastAPI for AI solutions. - Strong problem-solving, analytical, and communication skills. Preferred Skills : - Experience with AI-powered chatbots and OpenAI API integration. - Exposure to LLMs (GPT, LLaMA, Falcon, etc.) for real-world applications. - Hands-on experience in generative AI models.

About the job : We are looking for a highly skilled Senior AI/ML Engineer with 5+ years of experience to join our team. The ideal candidate should have extensive expertise in machine learning, deep learning, and AI model development, along with a strong background in Python, NLP, computer vision, and cloud-based AI solutions. Key Responsibilities : - Design, develop, and deploy AI/ML models for real-world applications. - Work with NLP, deep learning, and traditional ML algorithms to solve complex business problems. - Develop end-to-end ML pipelines, including data preprocessing, feature engineering, model training, and deployment. - Optimize model performance using hyperparameter tuning and model evaluation techniques. - Implement AI-driven solutions using TensorFlow, PyTorch, Scikit-learn, OpenAI APIs, Hugging Face, and similar frameworks. - Work with structured and unstructured data, performing data wrangling, transformation, and feature extraction. - Deploy models in cloud environments (AWS, Azure, or GCP) using SageMaker, Vertex AI, or Azure ML. - Collaborate with cross-functional teams to integrate AI models into production systems. - Ensure scalability, performance, and efficiency of AI/ML solutions. - Stay updated with emerging AI trends and technologies to drive innovation. Required Skills : - Strong experience in machine learning, deep learning, NLP, and AI model development. - Proficiency in Python, TensorFlow, PyTorch, Scikit-learn, and OpenAI GPT models. - Expertise in NLP techniques (Word2Vec, BERT, transformers, LLMs, text classification). - Hands-on experience with computer vision (CNNs, OpenCV, YOLO, custom object detection models). - Solid understanding of ML model deployment and MLOps (Docker, Kubernetes, CI/CD for ML models). - Experience in working with cloud platforms (AWS, Azure, GCP) for AI/ML model deployment. - Strong knowledge of SQL, NoSQL databases, and big data processing tools (PySpark, Databricks, Hadoop, Kafka, etc. - Familiarity with API development using Django, Flask, or FastAPI for AI solutions. - Strong problem-solving, analytical, and communication skills. Preferred Skills : - Experience with AI-powered chatbots and OpenAI API integration. - Exposure to LLMs (GPT, LLaMA, Falcon, etc.) for real-world applications. - Hands-on experience in generative AI models.

What will your day look like? - Leading a dynamic team to deliver high impact risk solutions across credit risk (underwriting, exposure controls and line management). - Work with stakeholders across product management, data science, and engineering to build relationship with the partner teams and drive implementation of risk strategies - Manage challenging time constraints to ensure on-time delivery of projects. - Work closely with partner teams in identifying, evaluating, and recommending new data that helps in risk differentiation. - Analyze loss trends and simulate risk decisioning strategies that help optimize revenue, approval rates etc. - Work closely with data science team and recommends credit risk decisioning and model deployment strategy. - Build a risk scorecard that leverages both internal performance data and external performance data that will be leveraged for credit decisioning at both underwriting and account management reviews for existing customers. - Collates analysis and builds presentations that helps articulate the risk strategy for the leadership team. To Help Us Level Up, You Will Ideally Have : - Quantitative background in engineering, statistics, math, economics, business, or related disciplines. - 5+ years experience in analyzing data and using database query language (e. SQL) analysis and programming and developer tools such as Python, R, data bricks in a finance or analytics field. - 2+ years of experience in leading high performing team of analysts. - Experience in working with non-traditional data such as social media will be a big plus. - Prior model building experience is a plus but not critical. - Possesses an analytical mindset and strong problem-solving skills. - Attention to detail and ability to multitask. - Comfortable working in a fast-paced environment and dealing with ambiguity. - Possesses strong communication, interpersonal and presentation skills; and ability to engage and collaborate with multiple stakeholders across teams. - Extremely proactive communicator willing to raise flags when needed and keep team members informed of ongoing risk or fraud related activities.

Responsibilities : Data Exploration and Insights : - Conduct continuous data exploration and analysis to identify opportunities for enhancing data matching logic, including fuzzy logic, and improving overall data quality within the SCI solution. - This includes working with large datasets from various sources, including Excel files and databases. Data Quality Improvement : - Perform various analyses specifically aimed at improving data quality within the SCI system. - This will involve identifying data quality issues, proposing solutions, and implementing improvements. Weekly Playback and Collaboration : - Participate in weekly playback sessions, using Jupyter Notebook to demonstrate data insights and analysis. - Incorporate new explorations and analyses based on feedback from the working group and prioritized tasks. Project Scaling and Support : - Contribute to the scaling of the SCI project by supporting data acquisition, cleansing, and validation processes for new markets. - This includes pre-requisites for batch ingestion and post-batch ingestion analysis and validation of SCI records. Data Analysis and Validation : - Perform thorough data analysis and validation of SCI records after batch ingestion. - Proactively identify insights and implement solutions to improve data quality. Stakeholder Collaboration : - Coordinate with business stakeholders to facilitate the manual validation of records flagged for manual intervention. - Communicate findings and recommendations clearly and effectively. Technical Requirements : - 5+ years of experience as a Data Scientist. - Strong proficiency in Python and SQL. - Extensive experience using Jupyter Notebook for data analysis and visualization. - Working knowledge of data matching techniques, including fuzzy logic. - Experience working with large datasets from various sources (Excel, databases, etc. - Solid understanding of data quality principles and methodologies. Skills : - SQL - Machine Learning (While not explicitly required in the initial description, it's a valuable skill for a Data Scientist and should be included) - Data Analysis - Jupyter Notebook - Data Cleansing - Fuzzy Logic - Python - Data Quality Improvement - Data Validation - Data Acquisition - Communication and Collaboration - Problem-solving and Analytical skills Preferred Qualifications (Optional, but can help attract stronger candidates) : - Experience with specific data quality tools and techniques. - Familiarity with cloud computing platforms (e.g., AWS, Azure, GCP). - Experience with data visualization tools (e.g., Tableau, Power BI). - Knowledge of statistical modeling and machine learning algorithms

Job Title : Data Scientist - AI Integration & Orchestration. Job Summary : We are seeking a skilled Data Scientist with expertise in AI orchestration and embedded systems to support a sprint-based Agile implementation focused on integrating generative AI capabilities into enterprise platforms such as Slack, Looker, and Confluence. The ideal candidate will have hands-on experience with Gemini and a strong understanding of prompt engineering, vector databases, and orchestration infrastructure. Key Responsibilities : - Develop and deploy Slack-based AI assistants leveraging Gemini models. - Design and implement prompt templates tailored to enterprise data use cases (Looker and Confluence). - Establish and manage an embedding pipeline for Confluence documentation. - Build and maintain orchestration logic for prompt execution and data retrieval. - Set up API authentication and role-based access controls for integrated systems. - Connect and validate vector store operations (e.g., Pinecone, Weaviate, or Snowflake vector extension). - Contribute to documentation, internal walkthroughs, and user acceptance testing planning. - Participate in Agile ceremonies including daily standups and sprint demos. Required Qualifications : - Proven experience with Gemini and large language model deployment in production environments. - Proficiency in Python, orchestration tools, and prompt engineering techniques. - Familiarity with vector database technologies and embedding workflows. - Experience integrating APIs for data platforms such as Looker and Confluence. - Strong understanding of access control frameworks and enterprise-grade authentication. - Demonstrated success in Agile, sprint-based project environments. Preferred Qualifications : - Experience working with Slack app development and deployment. - Background in MLOps, LLMOps, or AI system orchestration at scale. - Excellent communication skills and ability to work in cross-functional teams.

Data Scientist Responsibilities : Data Exploration and Insights : - Conduct continuous data exploration and analysis to identify opportunities for enhancing data matching logic, including fuzzy logic, and improving overall data quality within the SCI solution. - This includes working with large datasets from various sources, including Excel files and databases. Data Quality Improvement : - Perform various analyses specifically aimed at improving data quality within the SCI system. - This will involve identifying data quality issues, proposing solutions, and implementing improvements. Weekly Playback and Collaboration : - Participate in weekly playback sessions, using Jupyter Notebook to demonstrate data insights and analysis. - Incorporate new explorations and analyses based on feedback from the working group and prioritized tasks. Project Scaling and Support : - Contribute to the scaling of the SCI project by supporting data acquisition, cleansing, and validation processes for new markets. - This includes pre-requisites for batch ingestion and post-batch ingestion analysis and validation of SCI records. Data Analysis and Validation : - Perform thorough data analysis and validation of SCI records after batch ingestion. - Proactively identify insights and implement solutions to improve data quality. Stakeholder Collaboration : - Coordinate with business stakeholders to facilitate the manual validation of records flagged for manual intervention. - Communicate findings and recommendations clearly and effectively. Technical Requirements : - 5+ years of experience as a Data Scientist. - Strong proficiency in Python and SQL. - Extensive experience using Jupyter Notebook for data analysis and visualization. - Working knowledge of data matching techniques, including fuzzy logic. - Experience working with large datasets from various sources (Excel, databases, etc. - Solid understanding of data quality principles and methodologies. Skills : - SQL - Machine Learning (While not explicitly required in the initial description, it's a valuable skill for a Data Scientist and should be included) - Data Analysis - Jupyter Notebook - Data Cleansing - Fuzzy Logic - Python - Data Quality Improvement - Data Validation - Data Acquisition - Communication and Collaboration - Problem-solving and Analytical skills Preferred Qualifications (Optional, but can help attract stronger candidates) : - Experience with specific data quality tools and techniques. - Familiarity with cloud computing platforms (e.g., AWS, Azure, GCP). - Experience with data visualization tools (e.g., Tableau, Power BI). - Knowledge of statistical modeling and machine learning algorithms

About the job Position: Assistant Manager/Manager Credit Risk What will your day look like? - Leading a dynamic team to deliver high impact risk solutions across credit risk (underwriting, exposure controls and line management). - Work with stakeholders across product management, data science, and engineering to build relationship with the partner teams and drive implementation of risk strategies - Manage challenging time constraints to ensure on-time delivery of projects. - Work closely with partner teams in identifying, evaluating, and recommending new data that helps in risk differentiation. - Analyze loss trends and simulate risk decisioning strategies that help optimize revenue, approval rates etc. - Work closely with data science team and recommends credit risk decisioning and model deployment strategy. - Build a risk scorecard that leverages both internal performance data and external performance data that will be leveraged for credit decisioning at both underwriting and account management reviews for existing customers. - Collates analysis and builds presentations that helps articulate the risk strategy for the leadership team. To Help Us Level Up, You Will Ideally Have : - Quantitative background in engineering, statistics, math, economics, business, or related disciplines. - 5+ years experience in analyzing data and using database query language (e. SQL) analysis and programming and developer tools such as Python, R, data bricks in a finance or analytics field. - 2+ years of experience in leading high performing team of analysts. - Experience in working with non-traditional data such as social media will be a big plus. - Prior model building experience is a plus but not critical. - Possesses an analytical mindset and strong problem-solving skills. - Attention to detail and ability to multitask. - Comfortable working in a fast-paced environment and dealing with ambiguity. - Possesses strong communication, interpersonal and presentation skills; and ability to engage and collaborate with multiple stakeholders across teams. - Extremely proactive communicator willing to raise flags when needed and keep team members informed of ongoing risk or fraud related activities.

Responsibilities : Data Exploration and Insights : - Conduct continuous data exploration and analysis to identify opportunities for enhancing data matching logic, including fuzzy logic, and improving overall data quality within the SCI solution. - This includes working with large datasets from various sources, including Excel files and databases. Data Quality Improvement : - Perform various analyses specifically aimed at improving data quality within the SCI system. - This will involve identifying data quality issues, proposing solutions, and implementing improvements. Weekly Playback and Collaboration : - Participate in weekly playback sessions, using Jupyter Notebook to demonstrate data insights and analysis. - Incorporate new explorations and analyses based on feedback from the working group and prioritized tasks. Project Scaling and Support : - Contribute to the scaling of the SCI project by supporting data acquisition, cleansing, and validation processes for new markets. - This includes pre-requisites for batch ingestion and post-batch ingestion analysis and validation of SCI records. Data Analysis and Validation : - Perform thorough data analysis and validation of SCI records after batch ingestion. - Proactively identify insights and implement solutions to improve data quality. Stakeholder Collaboration : - Coordinate with business stakeholders to facilitate the manual validation of records flagged for manual intervention. - Communicate findings and recommendations clearly and effectively. Technical Requirements : - 5+ years of experience as a Data Scientist. - Strong proficiency in Python and SQL. - Extensive experience using Jupyter Notebook for data analysis and visualization. - Working knowledge of data matching techniques, including fuzzy logic. - Experience working with large datasets from various sources (Excel, databases, etc. - Solid understanding of data quality principles and methodologies. Skills : - SQL - Machine Learning (While not explicitly required in the initial description, it's a valuable skill for a Data Scientist and should be included) - Data Analysis - Jupyter Notebook - Data Cleansing - Fuzzy Logic - Python - Data Quality Improvement - Data Validation - Data Acquisition - Communication and Collaboration - Problem-solving and Analytical skills Preferred Qualifications (Optional, but can help attract stronger candidates) : - Experience with specific data quality tools and techniques. - Familiarity with cloud computing platforms (e.g., AWS, Azure, GCP). - Experience with data visualization tools (e.g., Tableau, Power BI). - Knowledge of statistical modeling and machine learning algorithms

Job Summary : We are seeking a skilled Data Scientist with expertise in AI orchestration and embedded systems to support a sprint-based Agile implementation focused on integrating generative AI capabilities into enterprise platforms such as Slack, Looker, and Confluence. The ideal candidate will have hands-on experience with Gemini and a strong understanding of prompt engineering, vector databases, and orchestration infrastructure. Key Responsibilities : - Develop and deploy Slack-based AI assistants leveraging Gemini models. - Design and implement prompt templates tailored to enterprise data use cases (Looker and Confluence). - Establish and manage an embedding pipeline for Confluence documentation. - Build and maintain orchestration logic for prompt execution and data retrieval. - Set up API authentication and role-based access controls for integrated systems. - Connect and validate vector store operations (e.g., Pinecone, Weaviate, or Snowflake vector extension). - Contribute to documentation, internal walkthroughs, and user acceptance testing planning. - Participate in Agile ceremonies including daily standups and sprint demos. Required Qualifications : - Proven experience with Gemini and large language model deployment in production environments. - Proficiency in Python, orchestration tools, and prompt engineering techniques. - Familiarity with vector database technologies and embedding workflows. - Experience integrating APIs for data platforms such as Looker and Confluence. - Strong understanding of access control frameworks and enterprise-grade authentication. - Demonstrated success in Agile, sprint-based project environments. Preferred Qualifications : - Experience working with Slack app development and deployment. - Background in MLOps, LLMOps, or AI system orchestration at scale. - Excellent communication skills and ability to work in cross-functional teams.

About the job : We are looking for a highly skilled Senior AI/ML Engineer with 5+ years of experience to join our team. The ideal candidate should have extensive expertise in machine learning, deep learning, and AI model development, along with a strong background in Python, NLP, computer vision, and cloud-based AI solutions. Key Responsibilities : - Design, develop, and deploy AI/ML models for real-world applications. - Work with NLP, deep learning, and traditional ML algorithms to solve complex business problems. - Develop end-to-end ML pipelines, including data preprocessing, feature engineering, model training, and deployment. - Optimize model performance using hyperparameter tuning and model evaluation techniques. - Implement AI-driven solutions using TensorFlow, PyTorch, Scikit-learn, OpenAI APIs, Hugging Face, and similar frameworks. - Work with structured and unstructured data, performing data wrangling, transformation, and feature extraction. - Deploy models in cloud environments (AWS, Azure, or GCP) using SageMaker, Vertex AI, or Azure ML. - Collaborate with cross-functional teams to integrate AI models into production systems. - Ensure scalability, performance, and efficiency of AI/ML solutions. - Stay updated with emerging AI trends and technologies to drive innovation. Required Skills : - Strong experience in machine learning, deep learning, NLP, and AI model development. - Proficiency in Python, TensorFlow, PyTorch, Scikit-learn, and OpenAI GPT models. - Expertise in NLP techniques (Word2Vec, BERT, transformers, LLMs, text classification). - Hands-on experience with computer vision (CNNs, OpenCV, YOLO, custom object detection models). - Solid understanding of ML model deployment and MLOps (Docker, Kubernetes, CI/CD for ML models). - Experience in working with cloud platforms (AWS, Azure, GCP) for AI/ML model deployment. - Strong knowledge of SQL, NoSQL databases, and big data processing tools (PySpark, Databricks, Hadoop, Kafka, etc. -Familiarity with API development using Django, Flask, or FastAPI for AI solutions. - Strong problem-solving, analytical, and communication skills. Preferred Skills : - Experience with AI-powered chatbots and OpenAI API integration. - Exposure to LLMs (GPT, LLaMA, Falcon, etc.) for real-world applications. - Hands-on experience in generative AI models.

Joining : Immediately. Job Role Responsibility Description : We are looking for passionate, Strong experience with an entrepreneur mindset to join us as Hardcore Full Stack Data Scientist end-to-end single-handed multi-hat role who is already working in applied AI in ML, deep Learning, ANN, and CNN platform specifically working as single-handed doers or in a small Data Science Team with full end to end ownership of Data Science work commitment delivery as Data Scientist working in any reputed AI Data Science is driven Tech startup preferably in Healthcare. Required Skillsets : - Needs to have statistical, mathematical, and predictive modeling as well as business strategy skills to build the algorithms necessary to ask the right questions and find the right answers. - Need to be able to communicate their findings, orally and visually. - Need to understand how the products are developed and even more important, as big data touches the privacy of consumers, they need to have a set of ethical responsibilities.- - Need to have a natural desire to go beneath the surface of a problem. - Confident and self-secure as they more often than not will have to deal with situations where there is a lot of unknown. - Good knowledge & experience in Artificial Neural Network ( ANN ), AI conversational Chatbot & Needs to be able to write the required Algorithm and coding programming. - Preferably in different programming languages such as Python, Tensor Flow, Keras, AWS (ML and DL), Numpy, and Pytorch. In addition the need to be familiar with disciplines as follows : - Natural Language Processing, Machine learning, Conceptual modeling, Statistical analysis, Predictive Modeling, and Hypothesis testing. Data scientists should have at least some of the following capabilities : - Cleaning data, formatting data, Having the ability to query databases & perform statistical analysis, building AI Data Modelling, validating the AI Model, and deployment. - Being able to develop or program databases. - Having a good understanding of design & architecture principles. Qualification : B.Tech / M.Tech in CSE / Electrical / Electronics & Communication/ Maths & Computing /Statistics /BioTech/BioStat / Clinical Engineering in Data Science / Machine Learning from Top-rated Tech University / Top rated IIT /IIIT. Mandatory Requirement : Experience : - Post last qualification of at least 0 to 7 Years of strong experience exclusive in real Industry Projects in applied AI ML & Deep Learning Data Science in an early-stage AI Health startup at the role and designation as a single-handed full-stack Principal Data Scientist / Sr. Data Scientist. - Hardcore in ANN /Deep Learning /Machine Learning/NLP with at least 2-20 good Applied AI-oriented Applied Research Projects & applications with hardcore experience working on ANN, CNN, RNN, and deep learning in Digital Health startups to solve specific complex problems.

Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Hybrid (Bengaluru) Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: Alphametricx) (*Note: This is a requirement for one of Uplers' client - Technology, Information and Media) What do you need for this opportunity? Must have skills required: Cision, Experience in deploying machine learning models in production environments., Experience with media monitoring, Familiarity with media intelligence tools such as Meltwater, or media analytics platforms., or similar., Social Listening, Data Scientist, NLP Technology, Information and Media is Looking for: Job Title: Senior Data Scientist Location: Bangalore Job Type: Full-time Experience Level: Senior Client is hiring for the role of Senior or Lead Data Scientist Position to drive the business growth of our Analytics COE. We are looking at the aspirant with a proven track record of solutioning & delivering NLP solutions to Fortune 500 companies. This individual will be responsible for building unique solutions and also deliver based on the set SLAs Job Summary: As a Senior Data Scientist, you will lead the development and optimization of advanced analytics tools, with a focus on media intelligence solutions. Your work will involve analyzing large data sets from various media channels, designing algorithms to track trends, and providing actionable insights. We are looking for someone with a strong background in building media analytics or intelligence tools, combined with excellent problem-solving skills and a passion for innovation. Key Responsibilities: Lead the design and development of analytics platforms and media intelligence tools, transforming large, unstructured data into meaningful insights. Develop machine learning models for trend detection, sentiment analysis, keyword extraction, and content recommendation. Work with large-scale media data from sources such as social media, news, blogs, and other online platforms. Collaborate with cross-functional teams, including data engineers, software developers, and product managers, to deliver end-to-end solutions. Implement NLP techniques to analyze and categorize media content from multiple sources. Build and optimize data pipelines for efficient data processing, storage, and retrieval. Translate business objectives into data-driven solutions and deliver actionable insights to internal teams and clients. Mentor and guide junior data scientists, providing support in developing their technical skills and career growth. Stay updated on the latest trends in data science, AI, and media intelligence to ensure the tools and platforms remain at the cutting edge. Required Skills and Qualifications: Proven experience (7+ years) as a Data Scientist, preferably in the media intelligence or analytics tool development domain. Strong expertise in machine learning, NLP, and statistical modeling. Hands-on experience with media data analysis, including sentiment analysis, keyword analysis, and audience engagement tracking. Proficiency in Python, R, and SQL. Familiarity with big data tools such as Hadoop, Spark, Redis, Apache Flink, and cloud platforms (AWS, GCP, Azure). Strong understanding of data pipelines and experience with data processing frameworks. Ability to work with large, unstructured data sets and develop models that derive actionable insights. Excellent problem-solving skills and the ability to deliver solutions in a fast-paced environment. Strong communication and presentation skills, with the ability to explain complex data insights to non-technical stakeholders. A Master's or PhD in Data Science, Computer Science, Statistics, or a related field. Preferred Skills: Experience with media monitoring, social listening, or media analytics platforms. Experience in deploying machine learning models in production environments. Familiarity with media intelligence tools such as Meltwater, Cision, or similar. Benefits: Competitive salary and bonus structure. A collaborative work environment with access to cutting-edge technologies.

What will your day look like? - Leading a dynamic team to deliver high impact risk solutions across credit risk (underwriting, exposure controls and line management). - Work with stakeholders across product management, data science, and engineering to build relationship with the partner teams and drive implementation of risk strategies - Manage challenging time constraints to ensure on-time delivery of projects. - Work closely with partner teams in identifying, evaluating, and recommending new data that helps in risk differentiation. - Analyze loss trends and simulate risk decisioning strategies that help optimize revenue, approval rates etc. - Work closely with data science team and recommends credit risk decisioning and model deployment strategy. - Build a risk scorecard that leverages both internal performance data and external performance data that will be leveraged for credit decisioning at both underwriting and account management reviews for existing customers. - Collates analysis and builds presentations that helps articulate the risk strategy for the leadership team. To Help Us Level Up, You Will Ideally Have : - Quantitative background in engineering, statistics, math, economics, business, or related disciplines. - 5+ years experience in analyzing data and using database query language (e. SQL) analysis and programming and developer tools such as Python, R, data bricks in a finance or analytics field. - 2+ years of experience in leading high performing team of analysts. - Experience in working with non-traditional data such as social media will be a big plus. - Prior model building experience is a plus but not critical. - Possesses an analytical mindset and strong problem-solving skills. - Attention to detail and ability to multitask. - Comfortable working in a fast-paced environment and dealing with ambiguity. - Possesses strong communication, interpersonal and presentation skills; and ability to engage and collaborate with multiple stakeholders across teams. - Extremely proactive communicator willing to raise flags when needed and keep team members informed of ongoing risk or fraud related activities.