3130 Pandas Jobs - Page 34

Python Programming: Proficiency in Python, Working with libraries like TensorFlow, PyTorch,Transformers,NLTK,Pandas,sklearn, and other related libraries used in NLP tasks and fine tuning language models. Experience with building comprehensive python modules for NLP tasks like tokenization, word embeddings,classifications. Evaluating and selecting the open source and/or commercial LLMs suitable for financial lending domains Location: Delhi NCR,Bangalore,Chennai,Pune,Kolkata,Ahmedabad,Mumbai,Hyderabad

Senior-Level Data Engineer Bachelors with 6+ or Masters with 5+ experience in Computer Science, Engineering, Math or other quantitative field. 5+ Experience with developing Batch ETL/ELT processes using SQL Server and SSIS ensuring all related data pipelines meets best-in-class standards offering high performance. 5+ experience writing and optimizing SQL queries and stored Procedures for Data Processing and Data Analysis. 5+ years of Experience in designing and building complete data pipelines, moving and transforming data for ODS, Staging, Data Warehousing and Data Marts using SQL Server Integration Services (ETL) or other related technologies. 5 + years' experience Implementing Data Wareho...

Programming: Python, R, Julia, SQL - Frameworks: TensorFlow, PyTorch, Scikit-Learn, Keras - Tools: Jupyter Notebooks, Vertex AI, AutoML, MLflow - Data Processing: BigQuery, Pandas, NumPy, Dask - Visualization: Matplotlib, Seaborn, Tableau, Power BI - Cloud: GCP AI Platform, Vertex AI, Cloud ML Engine - MLOps: Kubeflow, Vertex Pipelines, Docker, Kubernetes

Programming: Python, R, Julia, SQL - Frameworks: TensorFlow, PyTorch, Scikit-Learn, Keras - Tools: Jupyter Notebooks, Vertex AI, AutoML, MLflow - Data Processing: BigQuery, Pandas, NumPy, Dask - Visualization: Matplotlib, Seaborn, Tableau, Power BI - Cloud: GCP AI Platform, Vertex AI, Cloud ML Engine - MLOps: Kubeflow, Vertex Pipelines, Docker, Kubernetes

Programming: Python, R, Julia, SQL - Frameworks: TensorFlow, PyTorch, Scikit-Learn, Keras - Tools: Jupyter Notebooks, Vertex AI, AutoML, MLflow - Data Processing: BigQuery, Pandas, NumPy, Dask - Visualization: Matplotlib, Seaborn, Tableau, Power BI - Cloud: GCP AI Platform, Vertex AI, Cloud ML Engine - MLOps: Kubeflow, Vertex Pipelines, Docker, Kubernetes

Programming: Python, R, Julia, SQL - Frameworks: TensorFlow, PyTorch, Scikit-Learn, Keras - Tools: Jupyter Notebooks, Vertex AI, AutoML, MLflow - Data Processing: BigQuery, Pandas, NumPy, Dask - Visualization: Matplotlib, Seaborn, Tableau, Power BI - Cloud: GCP AI Platform, Vertex AI, Cloud ML Engine - MLOps: Kubeflow, Vertex Pipelines, Docker, Kubernetes

Programming: Python, R, Julia, SQL - Frameworks: TensorFlow, PyTorch, Scikit-Learn, Keras - Tools: Jupyter Notebooks, Vertex AI, AutoML, MLflow - Data Processing: BigQuery, Pandas, NumPy, Dask - Visualization: Matplotlib, Seaborn, Tableau, Power BI - Cloud: GCP AI Platform, Vertex AI, Cloud ML Engine - MLOps: Kubeflow, Vertex Pipelines, Docker, Kubernetes

Programming: Python, R, Julia, SQL - Frameworks: TensorFlow, PyTorch, Scikit-Learn, Keras - Tools: Jupyter Notebooks, Vertex AI, AutoML, MLflow - Data Processing: BigQuery, Pandas, NumPy, Dask - Visualization: Matplotlib, Seaborn, Tableau, Power BI - Cloud: GCP AI Platform, Vertex AI, Cloud ML Engine - MLOps: Kubeflow, Vertex Pipelines, Docker, Kubernetes

Programming: Python, R, Julia, SQL - Frameworks: TensorFlow, PyTorch, Scikit-Learn, Keras - Tools: Jupyter Notebooks, Vertex AI, AutoML, MLflow - Data Processing: BigQuery, Pandas, NumPy, Dask - Visualization: Matplotlib, Seaborn, Tableau, Power BI - Cloud: GCP AI Platform, Vertex AI, Cloud ML Engine - MLOps: Kubeflow, Vertex Pipelines, Docker, Kubernetes

Programming: Python, R, Julia, SQL - Frameworks: TensorFlow, PyTorch, Scikit-Learn, Keras - Tools: Jupyter Notebooks, Vertex AI, AutoML, MLflow - Data Processing: BigQuery, Pandas, NumPy, Dask - Visualization: Matplotlib, Seaborn, Tableau, Power BI - Cloud: GCP AI Platform, Vertex AI, Cloud ML Engine - MLOps: Kubeflow, Vertex Pipelines, Docker, Kubernetes

Programming: Python, R, Julia, SQL - Frameworks: TensorFlow, PyTorch, Scikit-Learn, Keras - Tools: Jupyter Notebooks, Vertex AI, AutoML, MLflow - Data Processing: BigQuery, Pandas, NumPy, Dask - Visualization: Matplotlib, Seaborn, Tableau, Power BI - Cloud: GCP AI Platform, Vertex AI, Cloud ML Engine - MLOps: Kubeflow, Vertex Pipelines, Docker, Kubernetes

- Programming: Python, R, Julia, SQL - Frameworks: TensorFlow, PyTorch, Scikit-Learn, Keras - Tools: Jupyter Notebooks, Vertex AI, AutoML, MLflow - Data Processing: BigQuery, Pandas, NumPy, Dask - Visualization: Matplotlib, Seaborn, Tableau, Power BI - Cloud: GCP AI Platform, Vertex AI, Cloud ML Engine - MLOps: Kubeflow, Vertex Pipelines, Docker, Kubernetes.

- Programming: Python, R, Julia, SQL - Frameworks: TensorFlow, PyTorch, Scikit-Learn, Keras - Tools: Jupyter Notebooks, Vertex AI, AutoML, MLflow - Data Processing: BigQuery, Pandas, NumPy, Dask - Visualization: Matplotlib, Seaborn, Tableau, Power BI - Cloud: GCP AI Platform, Vertex AI, Cloud ML Engine - MLOps: Kubeflow, Vertex Pipelines, Docker, Kubernetes.

- Programming: Python, R, Julia, SQL - Frameworks: TensorFlow, PyTorch, Scikit-Learn, Keras - Tools: Jupyter Notebooks, Vertex AI, AutoML, MLflow - Data Processing: BigQuery, Pandas, NumPy, Dask - Visualization: Matplotlib, Seaborn, Tableau, Power BI - Cloud: GCP AI Platform, Vertex AI, Cloud ML Engine - MLOps: Kubeflow, Vertex Pipelines, Docker, Kubernetes.

- Programming: Python, R, Julia, SQL - Frameworks: TensorFlow, PyTorch, Scikit-Learn, Keras - Tools: Jupyter Notebooks, Vertex AI, AutoML, MLflow - Data Processing: BigQuery, Pandas, NumPy, Dask - Visualization: Matplotlib, Seaborn, Tableau, Power BI - Cloud: GCP AI Platform, Vertex AI, Cloud ML Engine - MLOps: Kubeflow, Vertex Pipelines, Docker, Kubernetes.

- Programming: Python, R, Julia, SQL - Frameworks: TensorFlow, PyTorch, Scikit-Learn, Keras - Tools: Jupyter Notebooks, Vertex AI, AutoML, MLflow - Data Processing: BigQuery, Pandas, NumPy, Dask - Visualization: Matplotlib, Seaborn, Tableau, Power BI - Cloud: GCP AI Platform, Vertex AI, Cloud ML Engine - MLOps: Kubeflow, Vertex Pipelines, Docker, Kubernetes.

- Programming: Python, R, Julia, SQL - Frameworks: TensorFlow, PyTorch, Scikit-Learn, Keras - Tools: Jupyter Notebooks, Vertex AI, AutoML, MLflow - Data Processing: BigQuery, Pandas, NumPy, Dask - Visualization: Matplotlib, Seaborn, Tableau, Power BI - Cloud: GCP AI Platform, Vertex AI, Cloud ML Engine - MLOps: Kubeflow, Vertex Pipelines, Docker, Kubernetes.

Programming: Python, R, Julia, SQL - Frameworks: TensorFlow, PyTorch, Scikit-Learn, Keras - Tools: Jupyter Notebooks, Vertex AI, AutoML, MLflow - Data Processing: BigQuery, Pandas, NumPy, Dask - Visualization: Matplotlib, Seaborn, Tableau, Power BI - Cloud: GCP AI Platform, Vertex AI, Cloud ML Engine - MLOps: Kubeflow, Vertex Pipelines, Docker, Kubernetes

Programming: Python, R, Julia, SQL - Frameworks: TensorFlow, PyTorch, Scikit-Learn, Keras - Tools: Jupyter Notebooks, Vertex AI, AutoML, MLflow - Data Processing: BigQuery, Pandas, NumPy, Dask - Visualization: Matplotlib, Seaborn, Tableau, Power BI - Cloud: GCP AI Platform, Vertex AI, Cloud ML Engine - MLOps: Kubeflow, Vertex Pipelines, Docker, Kubernetes

Hiring manager and Recruiter should collaborate to create the relevant verbiage. Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Strong programming skills, with proficiency in Python and experience with AI frameworks such as TensorFlow, PyTorch, Keras or Hugging Face. Understanding in the usage of libraries such as SciKit Learn, Pandas, Matplotlib, etc. Familiarity with cloud platforms (e.g. Kubernetes, AWS, Azure, GCP) and related services is a plus. Experience and working knowledge in COBOL & JAVA would be preferred Having experience in Code generation, code matching & code translation Prepare the effort estimates, WBS,...

Role Overview: As an AI Engineer/SW Developer, you will be in a unique position to combine your strategic thinking with your technical skills in AI, machine learning, and data analytics. You will apply your skills to help implement data-driven solutions that align with business goals. You will steer enterprise projects that improve decision-making, solve complex problems, and drive business growth. This role involves working with team members and stakeholders to translate data insights into actionable recommendations that deliver meaningful business impact. Key Responsibilities: 1. Implement AI, Data Science, and Technical Execution: Support the design, implementation and optimization of AI-...

As Consultant, you are responsible to develop design of application, provide regular support/guidance to project teams on complex coding, issue resolution and execution. Your primary responsibilities include: Lead the design and construction of new mobile solutions using the latest technologies, always looking to add business value and meet user requirements. Strive for continuous improvements by testing the build solution and working under an agile framework. Discover and implement the latest technologies trends to maximize and build creative solutions Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise With 3-5yrs of Design...

As an Associate Data Scientist at IBM, you will work to solve business problems using leading edge and open-source tools such as Python, R, and TensorFlow, combined with IBM tools and our AI application suites. You will prepare, analyze, and understand data to deliver insight, predict emerging trends, and provide recommendations to stakeholders. In your role, you may be responsible for Implementing and validating predictive and prescriptive models and creating and maintaining statistical models with a focus on big data & incorporating machine learning. techniques in your projects Writing programs to cleanse and integrate data in an efficient and reusable manner Working in an Agile, collabora...

Scale an existing RAG code base for a production grade AI application RequirementsProficiency in Prompt Engineering, LLMs, and Retrieval Augmented Generation Programming languages like Python or Java Experience with vector databases Experience using LLMs in software applications, including prompting, calling, and processing outputs Experience with AI frameworks such as LangChain * Troubleshooting skills and creative in finding new ways to leverage LLM Experience with Azure Proof of Concept (POC) DevelopmentDevelop POCs to validate and showcase the feasibility and effectiveness of the proposed AI solutions. Collaborate with development teams to implement and iterate on POCs, ensuring alignmen...

Role Overview We are seeking a Machine Learning Data Scientist with hands-on experience in building, training, and deploying ML models that solve real-world business problems. The ideal candidate should be proficient in ML algorithms, feature engineering, model evaluation, and deployment, with strong programming and statistical skills. Required education Bachelor's Degree Preferred education Bachelor's Degree Required technical and professional expertise Key Responsibilities Work with stakeholders to understand business problems and translate them into ML solutions. Perform data exploration, cleaning, and feature engineering for structured and unstructured datasets. Build and validate models...