Business Data Analyst
Prove is the modern platform for continuous identity authentication and is used by over 1,000 enterprises and 500 financial institutions including 9 of the top 10 U.S. banks. Prove’s cloud solutions and mobile intelligence -driven APIs can be easily orchestrated to increase Approve Rates to over 90%, enabling companies to authenticate customer identities accurately, effortlessly, and privately, while mitigating fraud. Prove’s solutions are available in 195 countries. For the latest updates from Prove, follow us on LinkedIn.
As we continue to scale our company, we are looking for people who know how to make an impact. We’re talking self-starting professionals who thrive in a fast-paced environment, process information quickly and make intelligent decisions. The work is challenging and requires not only smarts, but natural curiosity and tenacity. Teamwork is also important to us – we work together and play together.
Prove has big plans; we’re excited and optimistic about the future. If this sounds like a career for you – come check us out.
As a 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 VP Solutions Delivery, 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.
With your data analysis skills, you will play a pivotal role in evaluating proof of concept results and synthesizing keen insights on customer experience challenges, fraud trends, key risk indicators, identity and authentication patterns, approval or rejection reasons, etc. You will apply your findings to suggest improvements to the prospect’s current operational process(es) utilizing Prove solutions to solve for their pain points.
You will work closely with the Sales Directors to build and present your findings and recommendations in a manner that helps our clients understand the quantitative benefit from using Prove solutions; including improvement in approvals, cost reduction, fraud capture, revenue gains and process improvement. Where applicable, you will help prospective clients redesign their current process to either replace or complement incumbent solutions with Prove solutions.
In addition, based on your analysis and findings, you will work closely with the Product and Engineering teams to make recommendations that improve Prove products and directly impact customer experiences. You will therefore play a pivotal role in shaping the future of identity verification and help us achieve our mission of creating a modern, state-of-the-art frictionless identity and authentication platform.
What You Are Accountable For
- Work with the respective Sales Director to understand a prospect’s unique business problems, use cases, and current gaps; as a result, assist in driving the proof of concept design and execution to yield deeper insight into these issues
- Work with the Data Science Team to communicate the proof of concept (POC) design and client expectations from Prove Solutions
- Analyze and interpret the results of the PoC to demonstrate the problem areas and gaps with a prospect’s current process and how Prove’s solutions meet or exceed the stated prospect’s objectives
- Work with the Sales Director to provide customer consumable communication which advises clear data driven recommendations on how and where Prove solutions can be applied to achieve objectives
- Synthesize data learnings into a compelling (re)design of a prospective client’s current process showing how Prove solutions may replace or complement incumbent solutions
- Assist in prototyping new analytics and machine learning models to understand customer and product behavior; and extract key insights that impact product decisions
- Work with our 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
- Minimum of 3 years of work experience in data analysis; which includes at least 1 year of 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)
- Working knowledge of data science concepts such as:
- Setting up a supervised modeling problem
- 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. are a plus
- Excellent written, verbal and presentation skills
- Cultural values of humility, passion, inclusion and leadership
- Bachelor's degree or a Master’s degree in a technical field.
The salary range for this role for Denver, Colorado only is $60,000-100,000. Offered salary will be determined by the applicant’s education, experience, knowledge, skills, and abilities, as well as internal equity and alignment with market data.
This position is eligible to participate in the annual incentive program. Prove’s Benefits include but are not limited to:
-Excellent health, dental, and vision insurance that begins on your first day of employment
-401(k) plan with company match
-Unlimited vacation time
This position description should not be considered the final description of the position. It should be assumed that we would, to some extent, structure responsibilities in accordance with the successful candidate’s capabilities and changing business conditions.
Prove is an equal opportunity employer committed to providing equal employment opportunity for all people regardless of race, color, religion, gender or sexual orientation, age, marital status, national origin, citizenship status, disability, veteran status or other personal characteristics.
