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# CODA Graduate Data Scientist

- **Company:** EdwardsUK Edwards Limited
- **Location:** Hemel Hempstead, UK
- **Experience:** Starter
- **Contract:** Internship / Graduate position
- **Skills:** Artificial Intelligence, Amazon Web Services, Business Analytics Applications, Data Analysis, Microsoft Azure, Business Intelligence Development, Big Data, Cloud Computing, Data Cleansing, Information Engineering, Extract Transform Load (ETL), Data Visualization, Python (Programming Language), Machine Learning, Microsoft Dynamics, NumPy, Oracle (Applications), Power BI, Tensorflow, SAP (Applications), SQL Databases, Tableau (Software), Transaction Data, Google Cloud, Feature Engineering, Pytorch, Prophet, Large Language Models, Random Forest, Model Validation, Git, Pandas, Scikit Learn, Coda, Information Technology, Data Analytics, Xgboost, Machine Learning Operations, Data Pipelines, Recurrent Neural Networks, Docker, Databricks
- **Published:** September 11, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=e231bfdb5378b99e

## About the Role

* Bachelor's or Master's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, Economics, Finance, or a related quantitative field.
 * 0-2 years of experience in data analytics, machine learning, or predictive modelling through industry experience, internships, academic projects, or research.
 * Exposure through academic projects, internships or practical experience to forecasting techniques such as ARIMA, SARIMA, Prophet, Exponential Smoothing, XGBoost, Random Forest, LSTM, Temporal Fusion Transformers, or similar time series models.
 * Proficiency in Python (Pandas, NumPy, Scikit-learn) and SQL for data analysis, data preparation, and model development.
 * Understanding of statistical concepts, exploratory data analysis, feature engineering, and model evaluation techniques.
 * Experience working with structured datasets and performing data cleaning, transformation, and validation.
 * Familiarity with data visualization tools such as Power BI, Tableau, or similar platforms.
 * Strong analytical and problem-solving skills with an ability to interpret data and generate actionable insights.
 * Good communication skills with the ability to explain analytical findings to both technical and non-technical stakeholders.
 * Eagerness to learn new technologies, machine learning techniques, and forecasting methodologies.

Good-to-have Skills

 * Sales, Finance or controlling domain exposure is a key advantage.
 * Experience with sales or financial business big data.
 * Experience of scrum agile way of working.
 * Academic, internship or project experience in anomaly detection, time-series analysis, forecasting or predictive modelling.
 * Familiarity with cloud platforms such as Azure, AWS, GCP or Databricks.
 * Exposure to ML frameworks such as Scikit-learn, TensorFlow, PyTorch, or similar tools.
 * Understanding of data engineering fundamentals, ETL processes, and data pipelines.
 * Exposure to MLOps tools and practices such as MLflow, Docker, Git, or CI/CD pipelines.
 * Exposure to GenAI and LLM-based solutions for automated insights, reporting, or data analysis.
 * Knowledge of ERP systems such as SAP, Oracle, or Dynamics 365.
 * Preferred Time Series Requirement
 * Hands-on experience through projects, internships, or coursework in developing forecasting models and analyzing time-dependent data, including trends, seasonality, and business drivers.
 * Ability to evaluate forecast accuracy using metrics such as MAE, RMSE, MAPE, or similar measures.

## Description

* Analyse CODA datasets to identify unusual trends, data quality issues, reporting risks and potential business drivers.
 * Collaborate with Product Owner, business SMEs, controllers, data engineers and BI developers to translate reporting challenges into practical analytical solutions.
 * Build, apply and maintain statistical and machine learning models for CODA use cases, with an initial focus on anomaly detection across Sales and Finance transactional data, under the guidance and support of a Senior Data Scientist.
 * Support automation of recurring analytical checks for reporting cycles such as month-end close, using Python, SQL, and Databricks workflows to improve efficiency.
 * Document model logic, assumptions, limitations, controls and validation results to support trust, governance and knowledge sharing.
 * Provide clear explanations of analytical outputs so they can be understood by non-technical stakeholders and used in BI reports, analytics products and future AI-enabled capabilities.
 * Work with CODA data engineers to prepare data, validate inputs and support operationalisation in Databricks.
 * Define and test model features, thresholds, scoring logic and validation methods under the guidance of a Senior Data Scientist to improve accuracy, explainability and reduce false positives.