Associate Business Data Analyst at Prove (Formerly Payfone)
As an Associate Business Data Analyst working in Prove’s Revenue Team, you play a critical role in defining how Prove’s clients use our phone P(ossession), R(eputation), O(wnership) solutions.
Under the direction of the Business Intelligence Manager, and in partnership with the revenue and data science teams, you will analyze and interpret the results of client data studies; and then make recommendations based on your analysis to show clients how they may use Prove products to solve for their unique customer experience, fraud, identity verification, or consumer authentication challenges.You will work closely with the Revenue and Data Science teams to assist in the creation and maintenance of various BI reports, analysis, and PowerPoint presentations; data models and analytical tools to provide data analytical support to a wide range of internal and external stakeholders.
Where applicable, you will assist in the process of identifying prospective clients' current process to either replace or complement incumbent solutions with Prove solutions.
What You Are Accountable For
- Define and deliver metrics, reporting platforms, dashboards, and analytical models vital for tracking and managing the business
- Identify business challenges and initiate process improvement projects
- Assist in the creation of scalable processes and the identification of key performance indicators across Revenue, Marketing, Engineering, and Operations, etc.
- Responsible for gathering and cleaning of datasets across multiple data sources
- Assist in prototyping new analytics and machine learning models to understand customer and product behavior; and extract key insights that impact product decisions
- Assist our Business Intelligence, Product and Engineering teams to aid in the testing of new product ideas; and analyze the results to provide actionable recommendations that inform product strategy
Required Education & Experience
- Experience at a technology start-up or rapidly scaling company
- Solid understanding of statistical concepts and experience in applying them to solve business problems
- Experience in R or Python and experience in a scripting language (C-shell or Bash)
- Excellent written, verbal and presentation skills
- Cultural values of humility, passion, inclusion and leadership
- Understanding of Salesforce, Asana, Visio, Powerpoint, Tableau, and Jira
- Bachelor’s degree with relevant experience or Masters in related field
Working knowledge of data science concepts such as:
- Setting up a supervised modeling problem
- Understanding of NLP techniques for text representation, semantic extraction techniques, data structures and modeling
- Evaluating model performance through common metrics such as AUC, GINI, KS, etc.
- Advantages and disadvantages of various supervised modeling techniques such as Linear/Logistic Regression, Decision Trees, Ensemble Modeling, etc.
- Unsupervised modeling techniques such as K-means, PCA. LDA, etc.