326 to 350 of 620 Pandas Jobs

AWS/GCP Key skills and requirements: Demonstrated experience as a Data Engineer scaling Data heavy platforms Strong understanding of ETL pipelines and Data Architectures Python, SQL & Python libraries (Pandas & Spark) Modern Data Warehousing tools AWS/GCP experience Experience working in high-growth start-up or scale-up environments (essential) Hybrid working in Central London Pays £70k-£80k Unfortunately More ❯

AWS/GCP Key skills and requirements: Demonstrated experience as a Data Engineer scaling Data heavy platforms Strong understanding of ETL pipelines and Data Architectures Python, SQL & Python libraries (Pandas & Spark) Modern Data Warehousing tools AWS/GCP experience Experience working in high-growth start-up or scale-up environments (essential) Hybrid working in Central London Pays £70k-£80k Unfortunately More ❯

AWS/GCP Key skills and requirements: Demonstrated experience as a Data Engineer scaling Data heavy platforms Strong understanding of ETL pipelines and Data Architectures Python, SQL & Python libraries (Pandas & Spark) Modern Data Warehousing tools AWS/GCP experience Experience working in high-growth start-up or scale-up environments (essential) Hybrid working in Central London Pays £100k-£120k Unfortunately More ❯

Well-versed in Python. Strong team player. Strong communication skills. Software Developer tech stack: Python > 3.5 with type hints, data classes, and Flask REST API. Postgres for relational data, Pandas for data analysis, and Google Cloud Pub/Sub for messaging. Cloud Build for automated builds, and Cloud Run/Docker for containerisation. Google Cloud Platform is used for infrastructure. More ❯

via automated ML Ops. Ideally, you’ll also be technically skilled in most or all of the below: Expert knowledge of Python and SQL, inc. the following libraries: Numpy, Pandas, PySpark and Spark SQL Expert knowledge of ML Ops frameworks in the following categories: experiment tracking and model metadata management (e.g. MLflow) orchestration of ML workflows (e.g. Metaflow) data and … please email We reserve the right to close roles early when the particular role and/or location has had sufficient applications. Nice-to-have skills Python SQL Numpy Pandas PySpark YAML Terraform TensorFlow PyTorch Keras Scikit-learn Unit Testing Python Scripting Docker Kubernetes AWS S3 DynamoDB Immingham, England Work experience Machine Learning DevOps Languages English Seniority level Seniority level More ❯

is the right technical resolution to the business problems Minimum Qualifications 5+ years in an analytics or data engineering role Background in data analytics, proficient in SQL or Python Pandas Experience with data visualization tools, such as Tableau, GGplot, Keynote etc Fundamental understanding of statistical analysis, forecasting and modeling Preferred Qualifications Experience in coding for automation (e.g. Scala, Python, Java More ❯

via automated ML Ops. Ideally, you’ll also be technically skilled in most or all of the below: Expert knowledge of Python and SQL, inc. the following libraries: Numpy, Pandas, PySpark and Spark SQL Expert knowledge of ML Ops frameworks in the following categories: experiment tracking and model metadata management (e.g. MLflow) orchestration of ML workflows (e.g. Metaflow) data and … please email We reserve the right to close roles early when the particular role and/or location has had sufficient applications. Nice-to-have skills Python SQL Numpy Pandas PySpark YAML Terraform TensorFlow PyTorch Keras Scikit-learn Unit Testing Unix Scripting Docker Kubernetes AWS S3 DynamoDB Hull, England Work experience Machine Learning DevOps Languages English Seniority level Seniority level More ❯

via automated ML Ops. Ideally, you’ll also be technically skilled in most or all of the below: Expert knowledge of Python and SQL, inc. the following libraries: Numpy, Pandas, PySpark and Spark SQL Expert knowledge of ML Ops frameworks in the following categories: experiment tracking and model metadata management (e.g. MLflow) orchestration of ML workflows (e.g. Metaflow) data and … please email We reserve the right to close roles early when the particular role and/or location has had sufficient applications. Nice-to-have skills Python SQL Numpy Pandas PySpark YAML Terraform TensorFlow PyTorch Keras Scikit-learn Unit Testing Scripting Docker Kubernetes AWS S3 DynamoDB Derby, England Work experience Machine Learning DevOps Languages English Seniority level Seniority level Mid More ❯

s or PhD degree in a quantitative field. Proven experience of large-scale data analysis and hypothesis testing. Strong proficiency in statistical analysis and predictive modeling. Proficient in Python (pandas, scipy, numpy, scikit-learn) or R (tidyverse/data.table), along with SQL. Excellent problem-solving skills and attention to detail. Strong communication skills with the ability to present complex data More ❯

Mechanical or Electrical) or Agricultural Engineering. Professionally proficient in English (written and spoken) for non-English native speakers. Programming Skills: Proficient in Python, with experience in libraries such as Pandas, NumPy, Scikit-learn, Matplotlib, and others relevant to data science and analytics. Data Science Expertise: Background in predictive modeling, machine learning, and statistical analysis. API Integration: Experience in working with More ❯

s or PhD degree in a quantitative field. Proven experience of large-scale data analysis and hypothesis testing. Strong proficiency in statistical analysis and predictive modeling. Proficient in Python (pandas, scipy, numpy, scikit-learn) or R (tidyverse/data.table), along with SQL. Excellent problem-solving skills and attention to detail. Strong communication skills with the ability to present complex data More ❯

temporal modeling and deep learning. Document methods and support reproducibility, validation, and publication where appropriate. Essential Requirements Strong programming and modeling skills in Python (NumPy, PyTorch or TensorFlow, SciPy, pandas). In-depth knowledge of machine learning for time-series, including RNNs, LSTMs, GRUs, transformers, attention mechanisms. Solid understanding of probabilistic models (HMMs, Bayesian inference, graphical models). Experience designing More ❯

is highly preferred! Strong experience building and implementing forecasting models using modern ML techniques. Deep understanding of time series analysis, statistics, and forecasting methodologies. Production-level Python programming skills (Pandas, Polars, Scikit-learn, NumPy, SciPy). Comfort working in a collaborative, cross-functional environment. Please note, this role cannot offer sponsorship at this stage More ❯

and have a secret love for 'ARIMA models.' Qualifications: A strong background in mathematics, statistics, or a related field Proficiency in Python, with experience using libraries such as NumPy, Pandas, and Scikit-Learn Familiarity with high-frequency trading strategies and market microstructure The ability to stare at screens for extended periods of time without going blind A passion for solving More ❯

Must-Have Skills Solid experience with data engineering on AWS (Glue, S3) Strong knowledge of Elasticsearch (query design, aggregations, performance tuning...) Proficiency in Python, especially in data wrangling (PySpark, Pandas) Experience with data quality, schema evolution, and operational monitoring Familiarity with LLMs, embeddings, or search ranking improvements is a plus Backend development skills with Node.js or general JavaScript knowledge would More ❯

depth, business acumen, and excellent communication skills to convey insights effectively to clients and internal teams. Technical Skills: Proficiency with open-source tools and technologies. Languages & Libraries: Python, R, Pandas, NumPy, scikit-learn, XGBoost, LightGBM, statsmodels. NLP & ML Frameworks: spaCy, Hugging Face Transformers, TensorFlow or PyTorch (as applicable). Visualization tools: Plotly, Seaborn, Matplotlib, Dash, Streamlit. Preferred Qualifications: Fluency in More ❯

Washington DC/Northern Virginia with occasional travel to client sites. A degree in Computer Science or a related field. 3+ years of hands-on experience with Python coding (pandas, numpy, sklearn, TensorFlow, PyTorch, etc.). Proven experience deploying machine learning models into production environments. Proficiency with SQL/NoSQL databases, version control tools (e.g., Git), Docker, and Kubernetes. Strong More ❯

and again. Proven track record delivering impactful ML/AI solutions in production. Deep expertise in Python and modern AI/ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn, NumPy, Pandas). Hands-on experience with GenAI, agentic AI, and automated testing for AI systems. Curiosity and creativity to challenge assumptions and explore new approaches. Strong communication skills and a passion More ❯

and again. Proven track record delivering impactful ML/AI solutions in production. Deep expertise in Python and modern AI/ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn, NumPy, Pandas). Hands-on experience with GenAI, agentic AI, and automated testing for AI systems. Curiosity and creativity to challenge assumptions and explore new approaches. Strong communication skills and a passion More ❯

and again. Proven track record delivering impactful ML/AI solutions in production. Deep expertise in Python and modern AI/ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn, NumPy, Pandas). Hands-on experience with GenAI, agentic AI, and automated testing for AI systems. Curiosity and creativity to challenge assumptions and explore new approaches. Strong communication skills and a passion More ❯

strong desire to explore the potential and capabilities of AI as applied to data analysis & manipulation. What we’re looking for: 1- 3 years’ experience working w/Python (pandas, numpy etc) Salary – Up to £55,000 dependent on experience. Hybrid – Flexible 3 days in the office (London SE1 9SG) If this looks like the one for you, please apply. More ❯

to ensure the team delivers the highest standards of analysis and reporting to key stake holders Numeric degree ideally to Masters level (min 2:1) Working knowledge of Python, Pandas, NumPY, PyTest, Java and R Understanding of machine learning techniques, such as clustering, classification, and regression Previous experience presenting information to key stakeholders Nice to haves...... Previous experience using Generalised More ❯

Statistics, Quantitative Finance, or related field. Extensive experience in model validation, quantitative analysis, or risk analytics. Strong knowledge of market, credit, and liquidity risk frameworks. Proficiency in Python (NumPy, Pandas, etc.) and SQL for data analysis. Strong understanding of option pricing theory and statistical risk modelling techniques (VaR, Backtesting, Stress Testing). Excellent verbal and written communication skills. Industry certifications More ❯

s degree in a relevant field (e.g., Data Science, Applied Mathematics, Engineering, etc.). 2+ years of commercial data science or analytics experience (post-study). Proficiency in Python (pandas, numpy) and SQL . Strong experience building dashboards using Power BI . Great communication skills — you enjoy explaining complex things in simple terms. A natural curiosity and desire to experiment More ❯

s degree in a relevant field (e.g., Data Science, Applied Mathematics, Engineering, etc.). 2+ years of commercial data science or analytics experience (post-study). Proficiency in Python (pandas, numpy) and SQL . Strong experience building dashboards using Power BI . Great communication skills — you enjoy explaining complex things in simple terms. A natural curiosity and desire to experiment More ❯