3126 Matplotlib Jobs - Page 48

About AstraZeneca AstraZeneca is a global, science-led, patient-focused biopharmaceutical company that focuses on the discovery, development and commercialization of prescription medicines for some of the world’s most serious diseases. But we’re more than one of the world’s leading pharmaceutical companies. Position Title: Insights Manager This position is responsible for using customer-level data, sales data, profiling data, and other information to perform analysis which helps the business in designing an effective customer engagement plan. Spearhead the segmentation and targeting process, driven by strategy definition for the Business. Leverage the analysis to generate insights and recomm...

Evalueserve, a global leader in providing innovative solutions to a wide range of clients, including Fortune 500 companies, is seeking talented professionals to join their dynamic team. With a presence in over 45 countries, Evalueserve leverages cutting-edge technology, artificial intelligence, and deep subject matter expertise to elevate clients" business impact and strategic decision-making. The company's team of 4,500 professionals operates worldwide, with a strong emphasis on continuous learning, work-life balance, and equal opportunity for all. The Risk and Quant Solutions (RQS) practice at Evalueserve is rapidly expanding and addresses significant financial needs with proven technologi...

The responsibilities of this role include gathering data from various sources, such as databases, spreadsheets, and APIs. You will be tasked with identifying, cleaning, and transforming data to ensure accuracy, consistency, and integrity. Developing and maintaining data pipelines and processes for efficient data handling will be a crucial part of your duties. Conducting exploratory data analysis to identify trends, patterns, correlations, and anomalies is essential, along with applying statistical techniques and data visualization tools to analyze datasets. As a Data Analyst, you will interpret data and provide meaningful insights and recommendations. Developing and maintaining reports, dash...

Position Overview : IT Shaala is a premier training institute committed to empowering individuals with the skills needed to thrive in today’s tech-driven world. We specialize in delivering hands-on, industry-relevant training in IT and emerging technologies. We are seeking a passionate and skilled Data Analyst/Data Science Trainer to design, deliver, and facilitate training programs that equip learners with practical knowledge and hands-on experience in data analysis. The trainer will be responsible for teaching concepts, tools, and techniques related to data analytics/Data Science while mentoring learners to apply these skills in real-world scenarios. Requirements Required Skills : Conduct ...

Data Scientist (Openings across India – Remote, Hybrid, and On-site options available) About Us: Tallento.ai is India’s leading AI-powered recruitment and talent management platform , trusted by top brands, enterprises, and global MNCs . With over 1 million registered users and 5,000+ corporate and institutional clients , we leverage advanced AI, machine learning, and data analytics to deliver scalable solutions that are transforming the way talent connects with opportunity. Job Summary: We are hiring Data Scientists at all levels — from fresh graduates to senior experts — to build data-driven solutions and intelligent models that power our platform. As part of our tech team, you’ll work on ...

As a Senior AI/ML Engineer at HireNema, youll take ownership of end-to-end AI/ML solutions from research and prototyping to large-scale deployment. You'll be designing algorithms that not only perform at scale but also meet the highest standards for accuracy, transparency, and fairness. If you live and breathe Python and know how to turn data into real-world impact, this role is for you. Key Responsibilities Lead the design, development, and optimization of AI/ML models for candidate evaluation, scoring, and ranking Own the ML pipeline: data ingestion, preprocessing, feature engineering, model training, validation, deployment, and monitoring Build production-grade AI systems in Python with l...

About The Role Project Role : Data Science Practitioner Project Role Description : Formulating, design and deliver AI/ML-based decision-making frameworks and models for business outcomes. Measure and justify AI/ML based solution values. Must have skills : Data Science Good to have skills : NAMinimum 15 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As a Data Science Practitioner, you will be engaged in formulating, designing, and delivering AI and machine learning-based decision-making frameworks and models that drive business outcomes. Your typical day will involve collaborating with various teams to measure and justify the value of AI an...

Introduction In this role, you'll work in one of our IBM Consulting Client Innovation Centers (Delivery Centers), where we deliver deep technical and industry expertise to a wide range of public and private sector clients around the world. Our delivery centers offer our clients locally based skills and technical expertise to drive innovation and adoption of new technology. Your Role And Responsibilities 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 emergin...

Qualification:Computer Science or a related field. Experience:3 5 years. of Vacancy:1. Responsibilities. Develop and deploy computer vision algorithms and deep learning models for diverse problems. Design and implement computer vision models using state-of-the-art techniques and frameworks. Explore and analyze unstructured data like images through image processing. Analyze, evaluate and optimize existing computer vision systems to improve performance and accuracy. Test and validate computer vision code and models, ensuring robustness and reliability. Research and implement new computer vision technologies to stay at the forefront of the field. Collaborate with cross-functional teams to devel...

Job Overview: We are looking for a skilled Python and Data Science Programmer to develop and implement data-driven solutions. The ideal candidate should have strong expertise in Python, machine learning, data analysis, and statistical modeling. Key Responsibilities: Data Analysis & Processing: Collect, clean, and preprocess large datasets for analysis. Machine Learning: Build, train, and optimize machine learning models for predictive analytics. Algorithm Development: Implement data science algorithms and statistical models for problem-solving. Automation & Scripting: Develop Python scripts and automation tools for data processing and reporting. Data Visualization: Create dashboards and visu...

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.