Analyst, Data Science and Analytics- Credit Risk

This role involves diagnosing business needs, translating them into data-driven questions, and architecting data solutions. The analyst will work with data scientists and clients to uncover insights, communicate findings, and ensure quality delivery of analytic solutions. Key responsibilities include conducting data analysis, providing customer support, interpreting monitoring reports, and utilizing SAS/SQL for data manipulation and reporting. The position also focuses on analyzing big data for consumer journey insights and validating models.

Must Have

• Diagnose business needs for data solutions.
• Wrangle and analyze data from multiple sources.
• Identify and translate new insights.
• Execute best practices for analytic solutions.
• Conduct data analysis and interpret reports.
• Proficiency in SAS, SQL, and Excel.
• Manage data auditing and validation.
• Present analytical outputs to clients.
• Ensure model quality and validation.
• Analyze big data for consumer insights.
• Collaborate with teams and clients.
• Degree in relevant quantitative field.
• Strong logical and problem-solving skills.
• Excellent communication skills.
• Adaptability and fast learning.

Good to Have

• SAS experience
• SQL experience
• Business Object experience
• Dashboard creation experience

What We'll Bring:

Job description

Help diagnose business needs, translate into questions that Transunion will answer, and architect ways to wrangle data from multiple sources.

Work closely with Transunion’s data scientists, consultants, and external clients to identify new insights, translate findings into the stakeholder’s native language.

Execute cross-functional best practices ensuring quality delivery and instituting processes to improve efficiency of our analytic solutions.

Conduct data analysis to understand internal and client data, process flows, policies and procedures

Provides ongoing customer and sales support, uncovering opportunities and resolving problems

Constructs, analyses, and interprets various monitoring reports

Analyses and interprets trends encountered and makes logical conclusions from monitoring output

Utilizes communication and reporting methods to ensure the output and recommendations are presented to clients in an understandable manner

Read and import raw data from various formats into SAS environment. Use SAS to analyse data in detail as well as the utilization of macros

Generate tables and graphs using SAS and Excel

Scorecard and portfolio monitoring (SAS, SQL, Excel) and additional ad hoc analysis according to predefined techniques and standards

Managing the analysis of data files in various layouts and performing data auditing and validation

General and detailed data interrogation, transformation, and manipulation

Identification of data trends or patterns, data mining and warehousing

Ability to present outputs and recommendations to clients in an understandable manner

Working with senior data scientists and offshore associates to ensure model quality in terms of modelling methodologies, data / model validation metrics, actionable insights, and analytical/technical best practices.

Analysing big data sets to generate deep insights on paid media, organic media, market conditions, web navigations, and individuals’ propensities on multi-step conversion activities in the consumer journeys.

Telling stories to make complex things simple to understand and translate into measurable actions.

Validating model results and package them into insightful client-friendly reports on ROI analysis, forecasting, simulation and optimization.

Ensuring rigorous quality control and detect anomalies in the model with ongoing new data stream.

Participate analytics discussions in client meetings

Cross-functional collaboration and best practices

What You'll Bring:

Skills and Experience: A degree in Statistics, Mathematics, Actuarial science, Business Mathematics, or Informatics degree Sound understanding of statistical software. SAS, SQL, Business Object and Dashboard creation experience would be preferred. Technical aptitude with strong logical, problem solving, and decision-making skills. Proficiency in performing multiple tasks and dealing with changing deadline requirements required. Must have good verbal and written communication skills; strong listening and teamwork skills; and effective presentation and sales skills are also required. Must be focused, flexible, and organized. Ability and willingness to learn in a fast-paced environment and adapt to the situation. Ability to work with junior data scientists and offshore associates. This is a hybrid position and involves regular performance of job responsibilities virtually as well as in-person at an assigned TU office location for a minimum of two days a week.

Impact You'll Make:

N/a

This is a hybrid position and involves regular performance of job responsibilities virtually as well as in-person at an assigned TU office location for a minimum of two days a week.