Job Summary
As a Data Scientist, you will have the opportunity to analyze and extract insights from a world-class financial data asset. You’ll perform in-depth, consumer-level analytics, lead big data research and discovery projects, increase overall system accuracy, and automate important (but repetitive) tasks. In addition, you’ll design and execute operational tests and provide recommendations based on careful analysis, solid business acumen, and superior problem-solving skills. The ability to turn complicated analytic results into digestible and engaging stories will be important for success, as will superior ambiguity tolerance. Your strong analytic training and background, desire to create new and unique perspectives about consumer financial behavior, collaborative spirit, and hands-on approach to solving problems will mark you as an ideal candidate for this role.

Job Duties

• Ask, refine, and answer critical business questions that bolster MX’s capabilities and competitive position through the application of advanced analytic methods, logical inference, and creative problem solving.

• Build, enhance, and maintain predictive models and analytic strategies focused on consumer financial behavior.

• Contribute to, or lead, modeling projects, operational tests (e.g., A/B and multivariate), and data mining and exploratory work to produce actionable and novel insights and recommendations.

• Partner with stakeholder groups to understand market needs and drive data initiatives beyond our current product portfolio.

• Engage in independent research projects to uncover and understand new tools, methods, and approaches that can strengthen MX’s data science platform.

• Create new data assets to support data science project work.

• Develop short presentations to communicate key messages and findings to colleagues and senior leaders.

Job Requirements

• Master’s degree (Ph.D. preferred) in a quantitative discipline, with coursework in statistics, econometrics, or a related field.

• Three years of advanced analytics experience focused on improving core business metrics (e.g., revenue, EBITDA, or net income); extra points for work focused on customer satisfaction and engagement and/or product quality.

• Eighteen months of practical experience building a variety of predictive/machine learning/statistical models and tools from complex, specialized, or large data pools; familiarity with the logic of credit scoring would also be helpful.

• Exhibit exceptional attention to data quality and maintain high standards of statistical rigor across all analytical tasks, including feature derivation and analysis of data distributions.

• Experience with one or more structured programming languages for statistical and/or numeric computing (e.g., Python, R, or Scala) and database query languages (e.g., SQL).

• Demonstrated competence with (a) one or more of logistic regression, generalized linear models, or categorical data analysis and (b) multiple machine learning approaches (e.g., k-means clustering, SVM, random forest, or PCA).

• Critical thinking skills, intellectual curiosity, and a willingness to keep looking for better solutions.

• Drive to tackle demanding goals with enthusiasm, tenacity in the face of stubborn obstacles, and interest in pursuing personal and technical development alongside other commitments.

• Commitment to client needs and satisfaction, humility in the face of constructive, well-meaning feedback, and production of high-quality work that builds trust and confidence with stakeholders.

• Ability to follow analytical frameworks and project plans to achieve shared goals.

Compensation
The expected on-target earnings (OTE), which is comprised of a base salary and other forms of cash compensation, such as bonus or commissions is currently $120,000-$144,000. This pay range is just one component of MX's total rewards package. MX takes a number of factors into account when determining individual starting pay, including job and level they are hired into, location, skillset, peer compensation.

At MX, we seek to hire candidates who drive results and achieve successful outcomes. We utilize a hybrid work arrangement style, which may require both local and remote team members to be in the office when necessary, to kick off projects, hold cross team strategy meetings, or complete key deliverables. Remote team members will travel into the office four times per year, and MX covers travel expenses associated with this requirement. Both local and remote employees can take advantage of our incredible office space with onsite perks, company-paid meals, onsite massage therapists, sports simulator, gym, mother’s lounge, and meditation room.

MX is proudly committed to recruiting and retaining a diverse and inclusive workforce. As an Equal Opportunity Employer, we never discriminate based on race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, military or veteran status, status as an individual with a disability, or other applicable legally protected characteristics. We particularly welcome applications from veterans and military spouses. All your information will be kept confidential according to EEO guidelines. You may request reasonable accommodations by sending an email to [email protected].