Continued…

Sara Sheikhi

+61-450-***-*** • adc027@r.postjobfree.com • Sydney, Australia

Qualifications Profile

Solutions-oriented and highly motivated Data Scientist / Data Engineer with ability to leverage experience and extensive training to deliver exceptional results for high growth industries.

Readily match business objectives with available technologies to meet short- and long-range information management goals.

Excel at combining business experience with technical knowledge to become a voice for data when communicating across technical skill levels.

Passion for big data engineering, data pipeline, visualisation, data analysis, and data science techniques including machine learning, deep learning, and their applications in pattern recognition, anomaly detection, and text mining.

Proactively transform large, complex data sets into actionable pragmatic tools that further business objectives.

Experience in statistical analysis, quantitative analytics, forecasting and predictive analytics, deep learning as well as optimization of algorithms.

Core Competencies

Tools: Python, R, PySpark, SQL Server, Tableau, AWS SageMaker, Azure Machine Learning, Airflow, Microsoft BI Stack (SSIS, SSAS, SSRS), Matlab, Java, Hadoop, MapReduce, Hive, Pig, Pandas, Scikit-learn, Numpy, SciPy, ggplot2, Shiny, Matplotlib, Plotly, seaborn, Git Techniques: Supervised and Unsupervised Learning, Regression, SVM, LDA, Decision Trees, Random Forest, XGBoost, Light GBM, Perceptron, Hierarchical Clustering, K-NN, K-Means, Gradient Descent, Probabilistic Modelling (Expectation Maximization: Soft EM/Hard EM), Feature Engineering, PCA, t-SNE, Model Selection, Cross-Validation, Bootstrapping, Regularization, Boosting, Bagging, Neural Network, Autoencoder

Text Mining: NLTK, spaCy,Tokenizing, StopWords, Bigrams, N-grams, Stemming/Lemmatization, Normalization, TF*ID

Education and Credentials

Master of Data Science (2018)

Monash University, Melbourne, Australia

Certifications

Applied Business Intelligence (SSAS, SSIS, SSRS), Querying SQL Server, SQL Server Design (FAD

Institute)

Oracle (Sharif University, Laitec Inst.)

Data Mining with RapidMiner (Dayche Institute)

Master of Business Administration (2008)

Mazandaran University of Science & Technology, Babul, Iran Bachelor of Industrial Management (2004)

Institute of Damavand, Tehran, Iran

Experience Highlights

IRI Market Research, Sydney, Australia 2019 - Present Data Scientist

Incorporating data science techniques in retail industry; analyzing the consumers panel and retailers point of sale data in order to deliver the insights to the panel recruitment and the marketing teams. Technical Scope: Python, R, SQL Server

Performing data wrangling and exploratory data analysis over the panel and grocery data. Developing and applying different modelling techniques such as market basket analysis, clustering, classification, purchase prediction and forecasting on time-series. Using feature engineering and smoothing techniques to improve the model accuracy. Examining the model performance and visualizing the result. Sara Sheikhi Page 2

Producing ad-hoc reports and data analysis on promotional plans, market shares, etc. for different retailers in order to discover the trends and reveal the potential factors involved in their performance.

Weighting consumers (panelists) data to project the panel level on to the national level, which reflects the Australian demographics attributes such as income, gender, age, ethnicity, and household size. Monash University, Melbourne, Australia 2017 – 2018 Research Assistant

Contributed to two separate studies simultaneously during a 4-month period: Hybrid Edge-Cloud Fall Detection (in collaboration with IBM Research) and Risk Safety Data Analysis of Construction Sites. Technical Scope: Python, R, Matlab, Tableau

Hybrid Edge-Cloud Fall Detection: Collected continuous sequences of accelerometer data and annotated for subsequent accuracy evaluation of models. Performed different techniques for feature engineering, dimension reduction and smoothing techniques to eliminate signal noise. Examined accuracy and precision of models by applying anomaly detection algorithms and evaluating different variations. Outcome: Increased model accuracy from 56% to 88%.

Risk and Safety Data Analysis of Construction Site: Performed data wrangling on incident data and injuries sustained, integrating data from different sources to obtain clear insights and interpretations through visualizations and interactive maps. Teamed effectively with business stakeholders, working on-site, to prepare reports and present analysis results to clients. Outcome: achieved integrated clean dataset with appropriate visualizations for client demonstrations necessary to win business contract. Roham Gas, Tehran, Iran 2009 - 2016

SQL and Business Intelligence Developer, 2013 – 2016 Promoted after successful tenure within organization. Selected to support enterprise-wide needs and requirements for data warehousing to ensure optimal departmental performance. Technical Scope: SQL Server, SSIS, SSAS, SSRS, Microsoft Excel

Performed ETL processes in SSIS platform to create data warehouse and define and create required multidimensional model and SSAS data cubes.

Designed dashboards, required reporting, and performance indicators over cubes via SSRS.

Interfaced effectively with end users and non-technical stakeholders, discussing requirements to ensure design capabilities aligned with user needs.

Procurement Specialist, 2009 – 2013

Oversee order placement and manage vendor relationships to effectively obtain all necessary services for proper facility operation. Handle all purchase order creation, price negotiation (according to global market), and order tracking/management to ensure efficiency in system operations.

Ordered, tracked, and planned for product delivery, accounting for lead time, budget, cost, inventory shortages, etc.

Communicated with senior level management regarding all reporting metrics, anomalies, and discrepancies to ensure continuity in business services.

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