Data Analyst Senior

hace 4 días


Santiago de Chile Experian A tiempo completo

**Company Description**
Experian is a global data and technology company, powering opportunities for people and businesses around the world. We help to redefine lending practices, uncover and prevent fraud, simplify healthcare, create marketing solutions, and gain deeper insights into the automotive market, all using our unique combination of data, analytics and software. We also assist millions of people to accomplish their financial goals and help them save time and money.

We operate across a range of markets, from financial services to healthcare, automotive, agribusiness, insurance, and many more industry segments.

The Data Analyst will help support ongoing projects focused on data accuracy, consumer advocacy, and related analytics. You will handle complex analytic requests and collaborating with partners to identify opportunities for improving data quality, data delivery.

**Main Responsibilities**
- Analyze complex data trends across consumer, commercial, housing, and alternative credit data to create insights that inform strategic decisions.
- Deploy analytical workflows, scalable data pipelines, data science solutions, and machine learning models to enhance data quality and operational efficiency.
- Translate high-level requirements into clear technical specifications, data models, and process flow diagrams that support solution development.
- Communicate analytical findings through compelling storytelling, data visualizations, and executive-level presentations to guide partner decision-making.
- Collaborate with internal clients to assess and resolve data quality issues, offering expert guidance as part of established data remediation programs.
- Partner with teams including Data Ops, Product Development, Compliance, and Audit to gather insights and feedback that shape data-driven programs and product strategies.

You will report: Data Analytics Manager Senior.
**Qualifications**
- Bachelor's degree in Data Science, Computer Science, Engineering, Statistics, Applied Mathematics, or a related quantitative field; or equivalent practical experience.
- 5+ years of experience in analytics, SQL, and proficient in relational and distributed data systems such as Aurora, MySQL, Hive, Athena.
- Experience analyzing large datasets using tools like Alteryx, Python, SAS, R, AWS Glue.
- Experience building and delivering insights through data visualization and BI tools such as Tableau, Power BI, Qlik, and Microsoft excel (can write advanced macros) (can maintain complex spreadsheets)/PowerPoint.
- A deep Interest in data modeling, machine learning, or GenAI, and proficiency in tools such as Python (NumPy, pandas, scikit-learn, TensorFlow, PyTorch) and Spark.
- Familiarity with cloud platforms like AWS, Azure, or Google Cloud Platform (GCP). Prior experience in the consumer credit, lending, or financial services industry. Knowledge of data domains such as CRRG/Metro2 standards, public records, credit inquiries, and commercial credit data.

**Additional Information**

Our uniqueness is that we celebrate yours. Experian's culture and people are important differentiators. We take our people agenda very seriously and focus on what matters; DEI, work/life balance, development, authenticity, collaboration, wellness, reward & recognition, volunteering... the list goes on. Experian's people first approach is award-winning; World's Best Workplaces 2024 (Fortune Top 25), Great Place To Work in 24 countries, and Glassdoor Best Places to Work 2024 to name a few. Check out Experian Life on social or our Careers Site to understand why.

Experian is proud to be an Equal Opportunity and Affirmative Action employer. Innovation is an important part of Experian's DNA and practices, and our diverse workforce drives our success. Everyone can succeed at Experian and bring their whole self to work, irrespective of their gender, ethnicity, religion, colour, sexuality, physical ability or age. If you have a disability or special need that requires accommodation, please let us know at the earliest opportunity.


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