Data Analyst at Prove (Formerly Payfone)
| Greater Denver Area
Sorry, this job was removed at 11:10 a.m. (MST) on Saturday, December 19, 2020
Prove is the modern platform for continuous identity authentication and is used by over 1,000 enterprises and 500 financial institutions including 7 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.
Prove Data Analysts play a critical role in building the next generation of authentication products. You will work closely with the product, sales, and engineering teams to refine products that directly impact customer experiences. You’ll play a pivotal role in shaping the future of identity verification and help us achieve our mission of creating a state-of-the-art frictionless authentication platform.
What You Are Accountable For
- Lead customer Proof of Concepts (PoC), providing valuable insight for sales both before and during the PoC
- Assist in prototyping new analytics & machine learning models that provide insights to customers as well as enhances our product directly
- Provide customer consumable communications on complex data problems
- Work with product and engineering teams to aid testing of new product ideas and analyze results to provide actionable recommendations
- Perform deep analysis and build models to understand customer and product behavior, and extract key insights that impact product decisions
- Synthesize data learnings into compelling stories and communicate to stakeholders
- Monitor and help refine metrics for product efficacy and customer success
- Work with the broader data analytics team to find ways to scale our insights through better systems and automation
- Act as a strategic partner to product and engineering leaders to help prioritize opportunities and inform product strategy
What We Require
- Basic understanding of statistical concepts and experience in applying them
- Experience in R or Python and experience in a scripting language (C-shell or Bash)
- Excellent written, verbal and presentation skills
- Two to four years work experience in data analysis; 1+ years of experience at a technology, start-up or rapidly scaling company
- Working knowledge of basic 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
- Promote, maintain and enhance our cultural values of humility, passion, inclusion and leadership
- Strong passion for learning our products and markets through in-house and external training
- Bachelor's degree or a Master’s degree in a technical field
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.
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