Data Scientist (Finance & Accounting / Forecasting)

Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Engineering, or related technical field 3+ years of relevant experience in data science and analytics Adept in building and deploying time series models Familiarity with project management tools such as Jira Experience in cloud platforms and services such as DataBricks or AWS Proficiency with version control systems such as BitBucket Proficiency in Python programming Experience with big data frameworks such as PySpark Strong knowledge of data cleaning packages (pandas, numpy) Proficiency in machine learning libraries (statsmodels, prophet, mlflow, scikit-learn, pyspark.ml) Knowledge of statistical and data mining techniques such as GLM/regression, random forests, boosting, and text mining Competence in SQL and relational databases Experience using visualization tools such as Power BI Strong communication and collaboration skills

Apply statistical techniques for insights and model creation Explain complex models to stakeholders Visualize and present data using Power BI, ggplot, and matplotlib Explore internal datasets for business insights and write efficient code Manage project codebase using Git or equivalent Design scalable dashboards and analytical tools Build collaborative relationships with stakeholders Enable quick prototype creation and develop predictive models Communicate analytical findings clearly to non-technical audiences Mine and analyze data to improve forecasting accuracy and business strategies Monitor model performance and data accuracy Implement and evaluate model outcomes cross-functionally