11 of 11 Remote Pandas Jobs in the South East

senior client stakeholders Tech Stack You'll Work With BI Tools : Power BI, Tableau, Looker, Google Data Studio Data Warehousing : Snowflake, BigQuery, Redshift, SQL Server Languages : SQL, DAX, Python (Pandas, NumPy, Scikit-learn - desirable) CRM Systems : Salesforce, HubSpot, Dynamics 365, Zoho ETL Tools : dbt, Fivetran, Talend, Alteryx AI/ML Frameworks (Desirable): Azure ML, AWS Sagemaker, HuggingFace, OpenAI APIs Version More ❯

senior client stakeholders Tech Stack You'll Work With BI Tools : Power BI, Tableau, Looker, Google Data Studio Data Warehousing : Snowflake, BigQuery, Redshift, SQL Server Languages : SQL, DAX, Python (Pandas, NumPy, Scikit-learn - desirable) CRM Systems : Salesforce, HubSpot, Dynamics 365, Zoho ETL Tools : dbt, Fivetran, Talend, Alteryx AI/ML Frameworks (Desirable): Azure ML, AWS Sagemaker, HuggingFace, OpenAI APIs Version More ❯

dbt, Airflow) Experience with loyalty-programme analytics or CRM platforms Knowledge of machine-learning frameworks (scikit-learn, TensorFlow) for customer scoring Technical Toolbox Data & modeling: SQL, Python/R, pandas, scikit-learn Dashboarding: Tableau or Power BI ETL & warehousing: dbt, Airflow, Snowflake/Redshift/BigQuery Experimentation: A/B testing platforms (Optimizely, VWO More ❯

learning models at scale. Deep familiarity with core ML concepts (classification, time-series, statistical modeling) and their real-world tradeoffs. Fluency in Python and commonly used ML libraries (e.g. pandas, scikit-learn; experience with PyTorch or TensorFlow is a plus). Experience with model lifecycle management (MLOps), including monitoring, retraining, and model versioning. Ability to work across data infrastructure, from More ❯

tight deadlines whilst remaining organised Strong analytical approach to problems Technical skills: Proficiency in Python Proficiency with version control (Git) Familiarity with containerisation (Docker) Familiarity with data processing tools (Pandas, NumPy) Experience using machine learning frameworks like PyTorch or TensorFlow Familiarity with cloud platforms and their ML services Benefits: MOST IMPORTANT: Your career Mentorship from senior machine learning engineers Access More ❯

ingest data. Consult with internal and external stakeholders then deliver the solution. Experience required: STEM/Computer Science Degree OR sufficient commercial experience Good skills with Python. Use of Pandas is a bonus Experience building Data Pipelines/ETL using Python Experience consuming with REST API services 1 years + commercial experience with Python or languages such as JAVA, PHP More ❯

and reporting workflows Present clear, actionable pricing insights to commercial and executive stakeholders Must-Haves Master's in Statistics, Econometrics, Data Science or related quantitative field Expert in Python (pandas, scikit-learn) and advanced SQL for large-scale data manipulation Proven track record running A/B tests or causal analyses on pricing levers Excellent communication-able to explain complex More ❯

closely with both technical teams and business users. A self-starter who is proactive, detail-oriented, and committed to delivering value. Nice to Have: Some experience in Python (e.g., pandas, seaborn, matplotlib). Familiarity with cloud platforms (AWS, Azure). Previous exposure to transport/rail industry data or commercial systems. If you are interested in this role, please apply. More ❯

data analysis and validation. Analyse all datasets to ensure that each KPI is understood, and data is ready for modelling. Proficiency in using Excel/SQL/Python/Pandas to process, transform, create variables, and build models. Build base models according to the project specification, incorporating all drivers of KPIs, providing rationale for variables selection, understanding coefficients and contributions. More ❯

pricing strategy alongside product and business teams. Skills & Experience Essential: - PhD in a mathematics, statistics or quantitative field (or Master's with strong pricing experience). - Excellent Python and Pandas skills. - Strong understanding of machine learning principles (excluding deep learning). - Ability to work independently on complex mathematical problems. - Research-led mindset with a passion for optimisation. Desirable: - Experience with More ❯

experience of Bedrock, Sagemaker, Python and Pandas. Key Responsibilities: * Working experience LLMs under Bedrock and Sagemaker both Amazon * Python with APIs to ChatGPT * Strong coding skills using libraries like pandas, NumPy, scikit-learn, PyTorch, and Hugging Face Transformers. Key Skills & Experience: AWS Data Science Environment: Hands-on experience with Sage Maker, Lambda, Step Functions, S3, Athena. Model deployment and pipeline … OCR Use-Case Development: Proficiency with Amazon Tex-tract, Tesseract, and LLM-based OCR. Building document parsing pipelines, validations, and rule Python Proficiency: Strong coding skills using libraries like pandas, NumPy, scikit-learn, PyTorch, and Hugging Face Transformers. Writing clean, modular, and testable code. Traditional Machine Learning Models: Experience with regression (linear, ridge), classification (logistic regression, decision trees, random forests More ❯