Azadeh Almasi – Data Scientist

Azi Almasi

Data Scientist

Data Analyst

About me

Data Scientist & Analytics with 4+ years of experience delivering business-focused analytics and applied data science solutions across commercial and operational domains. My career spans applied data science and business analytics roles, allowing me to bridge predictive modelling with decision-focused analytics.

I have hands-on experience using Python and SQL for data analysis, statistical modelling, forecasting, and experimentation, and I enjoy working with complex datasets to uncover insights that drive measurable business impact. My work includes building predictive models, analysing experiments (A/B testing), and translating analytical outputs into clear, actionable recommendations for non-technical stakeholders.

I am particularly interested in roles where analytics and data science are applied pragmatically to real-world business problems, with an emphasis on interpretability, collaboration, and impact rather than theory alone.

Location: London
Address: West Drayton
Mobile: 07880864882
Email: Azadealmasi@gmail.com

My Expertise

Predictive Analytics & Applied ML

Building regression, classification, and time-series models to support customer analytics, churn reduction, and growth initiatives.

Data Analytics & BI

Delivering business-focused analytics through KPI reporting, dashboarding, and automation to support strategic and operational decisions.

Data Analysis & Statistics

Applying exploratory analysis, statistical testing, forecasting, and experimentation to uncover trends and evaluate performance.

Data Visualisation & Communication

Creating clear Power BI and Tableau dashboards and translating complex insights into actionable outcomes for stakeholders.

Resume

Experinece

MAY 2025 – Present

Data Scientist (Business Analytics)

Alexander Macclean

Work on commercial analytics projects, supporting decision-making through data-driven insights.
Use SQL and Python (Jupyter) to explore data, validate assumptions, and assess modelling options.
Conduct EDA to identify trends, outliers, and performance issues across campaigns and operations.
Build and maintain analytical datasets and reporting outputs used by multiple stakeholders.
Translate business questions into measurable success criteria and analytical approaches.
Developed and maintained Power BI and Tableau dashboards to monitor business and operational performance.

Key Achievements:

Increased stakeholder adoption of analytical outputs by 20% through clearer insights and interpretation.
Improved decision confidence by delivering consistent, well-validated analytical results.
Developed and maintained Power BI and Tableau dashboards to monitor business and operational performance.

SEP 2022 – MAY 2025

Data Scientist

SYNTECH

Applied data analysis, statistical modelling, and predictive analytics to support business, product, and operational decision-making.
Used Python and SQL to clean, transform, and analyse large datasets for insight generation and performance evaluation.
Built and evaluated predictive and analytical models (e.g., regression, classification, and time-series forecasting) to identify trends, risks, and growth opportunities.
Designed and analysed experiments (A/B testing) to assess the impact of product and marketing initiatives.
Translated complex analytical outputs into clear, actionable insights through reports and visualisations for non-technical stakeholders.
Collaborated with cross-functional teams to ensure analytical work aligned with business needs.

Key achievements:

Improved customer retention by 15% through behavioural analysis and predictive modelling.
Contributed to optimisation initiatives that led to a 12% increase in conversion rates.

SEP 2017 – OCT 2018

Associate Data Analyst

Ordibehesht Studio

Conducted performance and market analysis using SQL, Python, and Excel to support commercial decision-making.
Built reports and dashboards to track key metrics, trends, and customer segments.
Collaborated with product and marketing teams to analyse user behaviour and performance drivers.
Supported on-demand analysis requests and contributed to documentation of analytical processes.

Key Achievements: