76 to 100 of 333 Pandas Jobs

products like Tableau, Microsoft Power BI and R Shiny. Research, design, and implement algorithms to solve complex problems. Program using R, Python (NumPy, SciPy, Pandas) or similar analytical languages. Perform data engineering, data processing and modeling techniques using cloud-based data management, data science, and ML platforms such as Databricks ...

Data Science, Data Visualization, Deep Learning, Graph Algorithms, Learning Agility, Machine Learning (ML), Machine Learning Algorithms, Nlp (Neuro-Linguistic Programming) And Genai, Organization Awareness, Pandas (Python), Python (Programming Language), R (Programming Language), Sql (Structured Query Language), Stakeholder Engagement, Statistical Analysis, Time Series AnalysisSummaryLocation: Cambridge (USA)Type: Full time ...

employed by ARU, you’ll be based at Cordell Health Limited’s premises in Portsmouth. Requirements Data Analytics & Machine Learning: including model development using Pandas, NumPy, Scikit-learn, or Tensor flow Programming Skills: Python, experienced in writing clean, modular, and reproducible code. Familiarity with data pipeline development, data base design ...

delivering production-ready models that drive measurable business value. Technical Proficiency: Strong expertise in Python and SQL. Deep familiarity with the Python data stack (pandas, NumPy, scikit-learn) and standard ML frameworks (such as PyTorch, XGBoost, or LightGBM). Engineering Rigor: Proven ability to build for production. Experience working ...

sample and genomic data. You have A BSc or MSc in computer science or related fields Expertise in Python, including popular Python libraries: NumPy, Pandas, PySpark and frameworks: Django, Django Rest Framework, FastAPI Hands-on experience with both relational (e.g. PostgreSQL) and non-relational databases (e.g. Elasticsearch, Redis) Extensive experience ...

experience with data, including querying, aggregation, analysis, and visualization* Strong competencies in Python for data analysis using the python data science libraries (Pandas/NumPy/SciPy/Scikit-learn).* Strong SQL skills for data retrieval, basic analysis, and data cleansing.* Strong knowledge and application of object-oriented design ...

sample and genomic data. You have A BSc or MSc in computer science or related fields Expertise in Python, including popular Python libraries: NumPy, Pandas, PySpark and frameworks: Django, Django Rest Framework, FastAPI Hands-on experience with both relational (e.g. PostgreSQL) and non-relational databases (e.g. Elasticsearch, Redis) Extensive experience ...

including Power Pivot, Power Query, DAX, data models and complex financial modelling. Working knowledge of Python for data manipulation and automation, for example using pandas and scripting against vendor APIs. Experience building or maintaining ETL and data pipelines and working with structured data at scale. Understanding of IT infrastructure ...

Strong knowledge of modern data science and machine learning techniques, including supervised and unsupervised learning. Proficiency in the Python data science ecosystem (e.g. NumPy, Pandas, scikit‐learn, PyTorch, TensorFlow). Experience with big data and distributed analytics platforms (e.g. Spark, Hadoop). Hands‐on experience with Natural Language Processing, graph ...

operating production data platforms, star-schema data models, and complex ELT/ETL pipelines.Advanced proficiency in Python and SQL, including clean object-oriented design, Pandas, query optimization, and REST API integrations.Hands-on experience within the Microsoft Azure ecosystem (Azure Data Factory, Azure SQL, ADLS), Azure DevOps, Git, CI/ ...

Strong knowledge of modern data science and machine learning techniques, including supervised and unsupervised learning. Proficiency in the Python data science ecosystem (e.g. NumPy, Pandas, scikit-learn, PyTorch, TensorFlow). Experience with big data and distributed analytics platforms (e.g. Spark, Hadoop). Hands-on experience with Natural Language Processing, graph ...

champion best practices in MLOps. What You Bring ·Proven experience building and iterating on ML models in a commercial setting. ·Expert-level Python skills (pandas, NumPy, scikit-learn, etc.) and strong statistical grounding. ·Experience working within cloud or modern data environments (Microsoft Fabric, Azure, or Databricks). ·Clear, impactful communication ...

navigate large, messy warehouses (BigQuery, Snowflake, Redshift, or similar) and write performant, readable queries. Solid Python (or R) for analysis and modeling: pandas, scikit-learn, statsmodels, and at least one deep-learning or gradient-boosting framework (XGBoost, LightGBM, PyTorch, TensorFlow). Experimentation fluency. You understand the math behind A/ ...

least 2 years’ experience working as a data engineer (ideally consulting/financial services) – salary and level will reflect experience. Proficiency in Python (pandas, numpy) Professional experience with Azure cloud services (AWS/GCP acceptable with deeper experience) Strong experience deploying clean, maintainable, production-level code. Basic understanding ...

Python; experience with R and/or C/C++ is a strong plus Extensive experience with numerical and data science libraries (e.g., NumPy, Pandas, SciPy, scikit-learn, PyTorch, TensorFlow, or similar) Proven experience building or maintaining machine learning systems in a distributed computing environment Proficiency developing in a Linux ...

life cycle processes and tools: CI/CD, version control (git), testing frameworks, MLOps. Experience with data science Python libraries such as Scikit-learn, Pandas, NumPy, Pytorch etc. Comfortable working with Docker and containerised applications Experience using AWS or similar cloud computing platform Experience delivering machine learning solutions within regulated ...

data pre- and post-processing, sampling and curation, ablation studies, evaluation Experience writing software using: i) Python for data science (numpy, scipy, scikit, pandas; ii) database; and iii) cloud platform services (AWS, GCP, Azure) NICE TO HAVES 5+ years experience in data science or related areas 2+ years tech lead ...

such as: data pre- and post-processing, sampling and curation, ablation studies, evaluationExperience writing software using: i) Python for data science (numpy, scipy, scikit, pandas; ii) database; and iii) cloud platform services (AWS, GCP, Azure)NICE TO HAVES5+ years experience in data science or related areas2+ years tech lead ...

insurance industry. Exposure to reinsurance, in particular casualty lines, would be a distinct advantage. Excellent Python skills, with demonstrable, production-quality experience using pandas and related libraries for data cleansing, transformation and automation. Experience with Git and collaborative development workflows. Strong SQL, with practical experience of designing relational database schemas ...

classical ML approaches, experimental design, and emerging AI/ML methodologies. Expert‐level Python proficiency with extensive experience using scientific and ML libraries (e.g., pandas, scikit‐learn, statsmodels, PyTorch/TensorFlow). Extensive hands‐on experience with large‐scale analytical data warehouses (BigQuery or equivalent). Experience defining modeling strategies ...

Extensive experience with traditional ML algorithms, Deep Learning frameworks, and complex time-series forecasting. Experience developing production-grade Python code: High proficiency in Python, Pandas, and modern software practices (testing, clean code, code review, CI/CD). Data & Pipeline Expertise: Hands-on experience optimizing data models and access patterns ...

area such as predictive modelling, classification, regression, optimisation or recommendation systems Strong proficiency in Python and open-source data libraries such as Pandas, NumPy and Scikit-learn A solid grounding in statistical methodologies, along with data extraction, manipulation and feature engineering techniques Experience with Spark, agile delivery methods ...

Extensive experience with traditional ML algorithms, Deep Learning frameworks, and complex time-series forecasting. Experience developing production-grade Python code: High proficiency in Python, Pandas, and modern software practices (testing, clean code, code review, CI/CD). Data & Pipeline Expertise: Hands-on experience optimizing data models and access patterns ...

evidence of curiosity and analytical rigour.Strong collaboration and communication skills in a research-driven environment.Deep familiarity with the Python numerical and data stack (NumPy, pandas, SciPy, scikit-learn, and modern columnar tooling such as Polars or DuckDB).Hands-on experience with agent frameworks, LLM APIs, and the design of evaluation ...

Master's degree in data science, statistics, mathematics, computer science, economics, engineering or a closely related quantitative discipline. Strong Python and SQL fundamentals, including pandas or comparable data‐analysis tools and the ability to work with relational data. Sound grasp of descriptive statistics, exploratory analysis, data visualisation, hypothesis testing ...