Sarah ***

CAREER SUMMARY

Data Scientist with 9 years of experience applying statistical analysis, machine learning and predictive modelling to solve complex business problems. Experienced in developing end-to-end data science solutions, from data preparation and exploratory analysis through to model development, deployment and performance monitoring. Strong background in Python, SQL, machine learning, experimentation and data visualisation, with proven experience communicating analytical insights to technical and business stakeholders.

EDUCATION

University of Sydney, Sydney NSW
Master of Data Science, February 2016 – December 2017

University of New South Wales, Sydney NSW
Bachelor of Science — Statistics and Mathematics, February 2012 – December 2015

EXPERIENCE

Data Insights Australia, Sydney NSW — Senior Data Scientist, January 2021 – Current

Lead end-to-end data science projects across customer analytics, forecasting and predictive modelling, working closely with product, engineering and business teams.
Develop and deploy machine learning models using Python, scikit-learn, XGBoost and other statistical modelling techniques to support data-driven decision making.
Build predictive models for customer behaviour, demand forecasting, churn prediction and business performance optimisation.
Design and analyse A/B tests and controlled experiments to measure the impact of product and marketing initiatives.
Perform exploratory data analysis and feature engineering across large structured datasets using Python, Pandas and SQL.
Develop automated data pipelines and model workflows to support repeatable analysis and production machine learning applications.
Create dashboards and analytical reports using Power BI and Tableau to communicate trends, model results and business insights to stakeholders.
Partner with software engineers and data engineers to integrate models into production systems and establish monitoring processes.
Present analytical findings to senior stakeholders, translating complex statistical results into clear business recommendations.
Mentor junior data scientists and analysts, reviewing analytical approaches, modelling methodologies and technical deliverables.

Analytics Solutions Group, Sydney NSW — Data Scientist, January 2018 – December 2020

Developed statistical and machine learning models to support customer segmentation, forecasting and business performance analysis.
Cleaned, transformed and analysed large datasets using Python, SQL, Pandas and NumPy.
Built classification and regression models using scikit-learn, XGBoost and statistical modelling techniques.
Conducted feature engineering, cross-validation and hyperparameter optimisation to improve model performance.
Designed customer segmentation models to identify behavioural patterns and support targeted business strategies.
Developed automated reporting workflows and dashboards using Tableau and Power BI.
Worked with business stakeholders to define analytical requirements and translate business questions into measurable data science problems.
Conducted statistical analysis and hypothesis testing to evaluate business initiatives and identify significant trends.
Documented modelling methodologies, assumptions, limitations and analytical results for technical and non-technical audiences.

Retail Analytics Co., Sydney NSW — Data Analyst, January 2016 – December 2017

Analysed customer, sales and operational datasets to identify trends, patterns and opportunities for business improvement.
Developed SQL queries to extract and transform data from relational databases.
Created recurring reports and dashboards using Excel, SQL and Tableau.
Performed exploratory data analysis and statistical analysis to support business and marketing decisions.
Built initial predictive models under the guidance of senior data scientists.
Automated repetitive reporting processes using Python, reducing manual data preparation and reporting effort.
Collaborated with business teams to define reporting requirements and communicate analytical findings.
TECHNICAL SKILLS

Programming: Python, SQL, R, Pandas, NumPy, SciPy

Machine Learning: Scikit-learn, XGBoost, LightGBM, classification, regression, clustering, feature engineering, model evaluation, hyperparameter optimisation

Statistics: Statistical modelling, hypothesis testing, A/B testing, regression analysis, probability, experimental design

Data Science: Exploratory data analysis, predictive modelling, customer segmentation, forecasting, feature engineering, data visualisation

Data & Databases: PostgreSQL, MySQL, SQL Server, data warehouses, ETL, data pipelines

Visualisation & BI: Tableau, Power BI, Matplotlib, Seaborn

Cloud & ML Platforms: AWS, Azure, Databricks, MLflow, Jupyter

Data Engineering: Python data pipelines, ETL workflows, data transformation, API integration

Professional Skills: Stakeholder management, analytical problem-solving, technical communication, requirements gathering, project leadership, mentoring

Education

2012-02 to 2015-12
Bachelor of Science — Statistics and Mathematics
University of New South Wales, Sydney NSW

2016-02 to 2017-12
Master of Data Science
University of Sydney, Sydney NSW

Skills

Data Science | Machine Learning | Predictive Modelling | Statistical Analysis | Python | SQL | R | Scikit-learn | XGBoost | Data Visualisation | Feature Engineering | A/B Testing | Hypothesis Testing | Customer Analytics | Forecasting | Data Mining | Data Pipelines | Tableau | Power BI | AWS | Azure | Databricks | MLflow

Occupation: Data Scientist

Experience: 9 years

Location: Sydney, New South Wales, Australia

Skills: Python, SQL, Analytics

Experience: 9 years

Daily rate: AUD 600

Fictional sample profile — replace with your approved candidate details.