Here are sample job advertisements for this type of role…
Predictive Analyst I
- Profitable growth,
- Improved competitive position,
- Use of cutting edge methods and forward thinking in development of new products,
- Maintenance of existing products with a fresh and ever-evolving point of view
- Join a world class group of statisticians, data scientists, mathematicians, and modelers on a mission to extract insights from information and put them to good use
- Contribute to projects involving descriptive, predictive, and prescriptive analysis leveraging a variety of statistical techniques (such as segmentation, regression, survival analysis, principal component analysis, scenario and sensitivity analysis, neural networks, and machine learning)
- Dig in by extracting data and performing segmentation and statistical analyses on large datasets (using languages/tools such as R, SAS, SQL, Hadoop and Python)
- Collaborate with internal and external partners to deliver innovative analytical products, solutions, and insights
- Assist with research and implementation of technology using machine learning and artificial intelligence techniques
- Train/coach team members/peers and actively share expertise
- Identify approaches and tools that can bring efficiencies or needed techniques to the team
- Communicate/present findings to R&D staff as well as business partners
- Bachelor’s Degree in a quantitative field, such as Statistics, Mathematics, Economics, Analytics, or other related fields with advanced coursework in statistics. Master’s Degree preferred
- Proficiency in one or more statistical programming languages such as SAS, Python, R, etc.
- Proven aptitude and demonstrated interest in statistical modeling techniques such as linear regression, logistic regression, GLM, etc.
- Robust analytical, critical thinking, and creative problem solving skills
- Strong time management skills with the ability to prioritize and contribute to multiple assignments simultaneously
- Solid written and verbal communication skills with the ability to clearly articulate ideas to both technical and non-technical audiences
- Proficiency with data visualization and graphics tools such as Tableau for the creation of reports and dashboards is a plus
- Professional analytical modeling experience, solving problems relevant to the insurance industry is desired, but not required
$53,000 – $90,000 a year
Credit Acceptance is proud to be an award-winning company! Our history of excellence and growth has resulted in many exciting career opportunities. For the 7th year in a row, we have been named one of Fortune Magazine’s 100 Best Companies to Work For. Our team members have created a world-class culture that promotes a positive workplace and drives us to succeed, making us one of the largest used car finance companies nationally.
Our IT and Analytics Team Members utilize the latest technology to develop, monitor, and maintain complex practices that help optimize our success. Our Team Members value being challenged, are encouraged to express their ideas, and have the flexibility to enjoy work life balance. We build intrinsic value by partnering with all functions of our business to support their success and make strategic business decisions. We focus on professional development and continuous improvement while enjoying a casual work environment and Great Place to Work culture!
The purpose of the Analyst, Predictive Analytics position is to analyze data to drive better business decisions, including: Pricing and credit risk, loan servicing strategies, business policies, processes, and performance, and champion/challenger tests.Outcomes and Activities:
- Test and implement models and data infrastructure used to execute strategy
- Actively monitor the performance of models in production
- Develop complex programming to extract and manipulate data
- Models and strategies: Develop, monitor, and maintain complex statistical models with the goal of optimizing high volume decisions to add intrinsic value to Credit Acceptance
- Reporting: Develop and produce reports to measure the performance of processes, models, and strategies
- Ad hoc analysis: Perform analysis to solve business problems and drive better decisions
- Translate business requirements: Translate high level business goals into the tasks and technical specifications needed to accomplish the goal
Knowledge and Skills:
- Knowledge of the auto lending industry and related analytical tools.
- Apply analytical skills to solve problems creatively.
- Act promptly and effectively when assigned tasks.
- Communicate complex information to others in a way they can understand.
- Work well with others in a team environment.
- Be proactive and make recommendations as opportunities arise.
- Be self-motivated and able to perform with minimal supervision.
- Be able to extract and manipulate large data sets.
Requirements:
- Bachelor’s degree or higher
- 1+ years’ experience with SAS and SQL (Associate)
- 3+ years’ experience with SAS and SQL (Analyst)
Preferred:
- Recent small company experience
- Experience developing credit scorecards or collection scores
- 1+ years’ experience in financial services analytics, or a combination of higher education and experience (Associate)
- 3+ years’ experience in financial services analytics, or a combination of higher education and experience (Analyst)
Targeted Compensation : $53,000 – $90,000
Responsibilities:Seeking a senior analyst for our telematics team to help optimize risk management services and underwriting solutions for our customers. In this role, you’ll work with aggregated telematics data in order to determine risky driving behavior, running these results through a series of algorithms to create our solutions which integrate into all aspects of NATL’s value chain. This role will be heavily involved with data acquisition, processing, and application of machine learning models, as well as pulling data from both new and familiar sources to quickly evaluate its efficacy. Furthermore, the candidate will need the ability to learn new tools on the fly and be adaptable to changing requirements.
- Technical SME for telematics data.
- Lead discussions with client stakeholders to understand business problems and formulate solutions
- Will work with IT acting in business analyst capacity to interpret product, claims and risk management requirements. Help prioritize the feature implementation pipeline
- Interpret data, analyze results using statistical techniques and provide ongoing insight, internally to business development leaders, externally to customers
- Telematics consultative services to internal (NATL) customers and in , including identifying and helping to resolve exposures with significant loss potential, investigating cause/effect of major losses and evaluating safety management programs.
- Lead data collection, wrangling and visualization efforts by maintaining high level of data integrity and accuracy.
- Conduct formal statistical analyses using R or relevant tools to interpret diagnostics information on telematics
- Work with PDM, OM and DA to whiteboard Telematics use cases and provide model based support for hypothesis testing
- Provide recommendations on implementing significant variables to existing product models – approach, implementation plan and release schema
- Lead discussions with technology, data-warehousing, other internal teams to resolve issues, deploy the models etc.
- Identifying, evaluating, and productionizing new data sources (e.g. geospatial data, web scraping, location services)
- Building anomaly detection models to determine unexpected trends in data, issues with data quality, etc.
Qualifications:
- 4+ years industry experience building predictive models in statistics, physical sciences, engineering, or other technical disciplines OR graduate-level research in relevant fields
- Strong programming skills (preference of Python OR R)
- Experience with query languages and SQL databases and/or NoSQL database’s such as MongoDB, Cassandra, HBase.
- Demonstrated experience in building, validating, and leveraging machine learning models
- Demonstrated skill with data mining, data munging, coping with missing/corrupt/ unstructured data
- Experience with at least some of the following: geospatial data tools, web scraping, merging with large external data sources
- Preferred: Experience handling Restful APIs calls using appropriate tools, JSON/ XML schema using relevant programming tools, big data tools (e.g. Hadoop, Spark) and cloud computing, version control system (TFS preferred) and building insurance pricing models