Decision Scientist Resume Samples

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Description :

1. Led a team of 5 members that worked alongside the Customer Insights team of a "Big 5" UK retailer Customer-Based Analytics o "Targeted Marketing Campaigns".
2. Provided recommendations for multiple targeted marketing campaigns run by the retailer after conducting rigorous data analysis.
3. Improved return on investment by over c.50% on certain campaigns by advising the retailer to changes in campaign dynamics.
4. Identified high spending customers (c.20% of customers) in the loyalty program who were not receiving their fair share of points and rewarded them appropriately to ensure their loyalty to the retailer Store-Based Analytics.
5. Carried out adjacency analysis to optimize store layout and helped the retailer improve product bundling.
6. Led to an increase in sales (c.2%) and footfall (c.4%) in stores where the new layout and bundles were implemented.
7. Created interactive visualizations (Tableau/Excel Power Maps) to understand the dynamics of customer shopping behavior within a region.

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Description :

1. Developing Analytical workbench using R and SAS - Building end-to-end analytical workbench with back end as R and SAS.
2. Delivery teams use this tool across the organization in providing solutions to the business problem at hand, reducing their coding efforts.
3. Worked on a pilot project with one of the large media channels who provide weather updates and one of the largest retailers.
4. Projects involved design and implementation of algorithm to drive weather-triggered advertising and optimization of online marketing budget respectively.
5. Predicted the weather conditions which influence sales of products for a Weather client.
6. Categorizing calendar year into seasons based on weather conditions in the markets of interest using K means clustering.
7. Identified the combination of metrics used to predict weather conditions that influence the sales of products using the Panel Data regression and OLS techniques.

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Description :

1. Led a team of 4 and drove a project to identify a prioritized list of target advertisers.
2. Served as a proactive customer engagement aid for our client.
3. Designed and implemented the entire reporting and analytics framework for the EMEA.
4. Led 4 analysts for one of the largest low-cost airlines.
5. Assisting their Strategy & Planning Team Forecast Fuel.
6. Identified the causes of delay and recommended mitigation strategy Industry.
7. Helped the marketing team.

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Description :

Provided pricing solutions using regression, and clustering techniques by identifying KPI's which led to $2M savings.Utilized analytics to drive client decision-making across the financial, airline, healthcare, insurance, and fitness verticals.Measured effectiveness.Performed passenger segmentation for the major domestic airline.Conducted prospective research on clinical trial data.Worked directly with the Marketing Analytics team of one of the largest PC manufacturers providing a comparative study of the competitors' products in the market and also an in-depth analysis stating the performance of their own products.Perform in-depth analysis of key business problems and analyze them quantitatively using statistical/mathematical methods.

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Description :

1. Deliver actionable insights and business recommendations through a hypotheses-based approach to problem-solving.
2. Deliver well-organized data analysis using dashboards, models, and trend analysis.
3. Analyze requirements and Research, Develop modules using statistical techniques in R and SAS Mentor peers in the team in SAS and R.
4. Design rules for MetricStream Social Media GRC system - Big Data Complete Solution.
5. Created multiple Categories with thousands of words and designed Rules using these categories to analyze the unstructured data to provide actionable intelligence to mitigate various risks.
6. Testing Rules and fixing.
7. Helped the retailer employ a uniform store layout across multiple stores within a region to improve footfall in-store (an increase of 5% across stores within a region).

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Description :

1. Improved the customer base of the retailer's online channel by c.3% by identifying customers who could be incentivized to shop online.
2. Understood online shopping patterns of customers and developed a visualization on QGIS (Quantum Geographic Information System).
3. Created a dashboard for promotions with promotion-dependent KPIs which helped the retailer cut costs by optimizing promotions to ensure maximum ROI.
4. Resulted in higher promotional participation and cutting costs by c.20%.
5. Actualized a CXO level interactive weekly business report in Tableau that recorded metrics corresponding to Orders and Revenue from Teradata.
6. Using different statistical methods including Modeling and Text Mining techniques in SAS and R to solve business problems across different verticals.
7. Telecom churn project which involved finding major factors affecting customers switching tendency to other competitors.

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Description :

1. After preparing the analytical dataset from individual months and performing some exploratory data analysis.
2. Led an 8-member engagement on a digital marketing analysis project, ranging from page-level and campaign reporting to content strategy, media spend.
3. Automated the data transfer from Google Analytics using Google API to the in-house database.
4. Played a key role in transitioning old reports to new ones.
5. Provided data mining and consulting services to a Fortune 25 Company to guide them in understanding key factors driving their sales.
6. Generated hypotheses and created regression models using SAS and MS Excel to perform data analysis.
7. Generated actionable insights and prepared reports and visualizations for client consumption and decision-making.

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Description :

1. Provide analytical consultation, predictive modeling, and solutions to achieve business goals and objectives.
2. Perform data collection, data cleaning, data validation, and reporting tasks for digital commerce systems and applications.
3. Perform exploratory data analysis to find fraud patterns and trends in business applications.
4. Design and develop advanced analytical data mining/machine learning algorithms and predictive models.
5. Validate analytic solutions to determine overall effectiveness.
6. Develop metrics to measure the incremental benefit/costs of competing analytic models.
7. Communicate analytic results to business partners.

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Description :

1. Identify and apply best practices in the field of advanced analytics (statistics, operations research, etc.).
2. Conduct research on analytical techniques and translate that research into usable and sustainable solutions.
3. Act as analytics consultant to business units within Starbucks.
4. Extracts data from various data platforms, including traditional relational database environments as well as next-gen cloud computing technologies (AWS, Azure).
5. Perform exploratory data analysis, cleanse, massage, and aggregate data.
6. Apply basic statistical concepts and descriptive statistics to understand and describe relationships in data.
7. In partnership with data science, builds predictive models and complex descriptive analytics, clustering, and market-based analysis.

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Description :

1. Design of experiments to support business understanding of the efficacy of campaigns and programs we initiative within the market that are customer-facing.
2. Provide analytic support (code documentation, data transformations, algorithms, etc.) to IT to implement analytic insights and recommendations into business processes (e.g., feed of modeling scores into campaign manager).
3. Contribute to analytic project proposals.
4. Evangelize the value of analytics and data among peers.
5. Apply knowledge of multidisciplinary business principles and practices to achieve successful outcomes in cross-functional projects and activities.
6. Business-applicable experience in several techniques for data visualization skills, e.g. Tableau / D3.
7. Working knowledge of basic statistical languages; experience with R, Python, SAS, SPSS, etc.