As a contracted Data Scientist for a marketing consultancy, I worked on projects across various clients spanning multiple industries.• Feature Engineering and Selection - Created a Random Forest Model to determine the relative importance of features for modeling customer retention for a client in the travel and leisure industry.• Data Analysis - Created a reporting dashboard of customer engagement and business cases for consolidation of branding for a client in the health care industry.• Modeling - Completed a Bayesian Mixed Media Model (using pymc-marketing package in Python) to optimize media spend across channels for a client in the commercial food service industry.

As a contracted Data Scientist I focused primarily on data validation and bug detection and reporting the results, as well as devising an ongoing monitoring regime.• Querying - Created SQL queries to test adherence to accepted business logic on data definitions and calculated fields.• Reporting - Using Hex, created visualizations and reports to convey the timing and nature of any data problems detected.• Accounting - Extended data auditing principles into the generation of accounting data reported out to customers.

As a Data Scientist, my focus was primarily on answering broad, strategic questions coming from senior leadership. These often had macroeconomic elements that required research beyond internal data sets. • Modeling: Created and maintained a macroeconomic drivers model to help senior leadership understand which macroeconomic variables have a material impact on revenue. Created spin-off models to address more focused areas of the business such as specific products. Forecasted revenue for the following fiscal year as a point of comparison to existing methodologies. • Forecasting: Created and maintained a seasonal ARIMA model to forecast volume for the next twelve months. • Project Management: Coordinated a location clustering project to better evaluate location performance relative to a group of peers.

As a Data Scientist, I optimized the customer outreach process and create comprehensive dashboards to ensure timely monitoring of the health of the marketing process through a number of campaigns.• Querying: Created complex queries for 10 separate data sources, including third-party vendors (Epsilon, Conversant, AWS). Queries written in Hive, postgresql, and Oracle.• Modeling: Created and deployed audience models based on business rules or developed with machine learning methods (DBSCAN, Random Forest, Naïve Bayes, XGBoost, KMeans) using Python and Alteryx.• Auditing: Verified accuracy of information across systems and diagnosed sources of variance. Audited output from customer lifetime value (gamma model). Debugged legacy SAS code used for traffic imputation calculations.• Reporting: Provided weekly reporting on store traffic and CCPA compliance.

As a student in the Operations Research and Supply Chain Management graduate program, I gained not only knowledge, but also hands-on experience in both fundamental and advanced areas of logistics and SCM. In addition, as a branch of the Weatherhead School of Management, business acumen and interpersonal skills were a critical focus of all aspects of the program. All businesses rely on customers, and the elements necessary for fruitful customer interactions and handling customer requests were covered in detail. In addition, I gained insight into presenting findings and business reviews at all levels within an organization, including managers and directors as well as executives. Developing buyers through purchasing pipelines as well as formulating achievable order promise dates were keys in demand planning. At the other end of the supply chain, we participated in projects geared toward targeted sourcing and commodity development, as well as the identification of strategic and/or growth suppliers.Optimization was taught in many key areas, including shipment route plan optimization and optimization through the analysis of route schedules and load plans. Throughput improvement and root cause analysis was discussed in detail from a production perspective, and end-to-end financial concepts were explored, including value-based management, spend projection and analysis, and purchase price variance (PPV). Measuring all aspects of performance, including delivery performance and quality performance via metrics dashboards, were highlighted, along with the overall concepts of Corporate Performance Management (CPM).

As a Six Sigma graduate student consultant, I worked collaboratively with other student team members to develop tactical processes to optimize supply chain operations using Lean Six Sigma best practices.• Route Optimization: Analyzed data and proposed transportation network changes to drive improvements in routing efficiency. Cross-referenced mean and standard deviation of delivery times from North American plants to warehouses with product distribution ratios.• Demand Planning: Reviewed annual volumes as laid out in customer agreements. Mapped forecast demand against actual demand, determined key trends, and assessed the implications on customer fulfillment. Created a continuous improvement simulation model in R that included three sources of variability to predict optimal safety stock levels, and suggested improvements based on the model.• Finance: Utilized data from annual spend databases to monitor, measure, and manage strategic cost savings opportunities. Identified and resolved problems related to continuous cost savings initiatives to minimize supply chain total cost of ownership with the ultimate goal of maximizing shareholder return.• Inventory: Assisted with inventory planning and management, including providing current inventory levels and predicting future inventory levels.

As a supply chain intern, I supported each facet of supply chain management, including demand forecasting, production optimization, supplier delivery, and cost tracking. This included a large project in which I programmed a “lite” version of the primary Supply Planning Engine in VBA, which allowed for increased features to external users while simultaneously safeguarding original data. This project required exceptional project management and organizational skills.• Process Management and Improvement: Followed standard processes and operating procedures where available. Mapped and documented new processes and business rules for improvement activities. Practiced problem-solving skills to execute acceptable solutions when problems were encountered, or proposed strategic and tactical solutions and escalated if required. Evaluated the effectiveness of solution design and implementation.• Production Optimization: Used independent judgement to create a linear optimization model for one of the factories to assist plant personnel in exploring the optimal daily production planning process and production scheduling in order to improve productivity. Used excellent written, verbal, and presentation skills to communicate the findings.• Demand Planning: Gathered and compiled purchasing data with great attention to detail. Utilized data mining techniques, including customer trends, to forecast sales and operations metrics.• Analytics: Automated the report creation processes for supplier scorecards and other performance reporting, reducing required work hours in some instances from hours to seconds. Developed timely and accurate ad hoc reports as required. Gathered supply chain data, including historical activity, for data analysis. Provided analytical support in the form of metrics and key performance indicators (KPIs) for large data sets.

• Took over investment research and portfolio proposal preparation to allow primary advisor to dedicate her time to client facing activities.• Rationalized equity and mutual fund holdings within book of business to help reduce administrative workload while simultaneously growing assets under management from $180MM to $270MM.• Increased trailing commissions on existing mutual fund holdings by 17% over two years by identifying and replacing underperforming, low value funds.

• Effectively cross-sold suitable credit products to qualified customers based on identified needs and credit history.• Exceeded targets for upselling add-on insurance products.

• Analyzed historical company financial records and interviewed company officers.• Prepared preliminary valuation reports, pricing analyses, confidential information memorandums, financial loss calculations, or other deliverables, as required.• Helped to write the Management Discussion & Analysis (MD&A) section of an IPO prospectus for a water utility company for whom XPS did annual goodwill impairment testing.