Data Scientist

You will be part of a very dynamic and fast-growing Analytics team at Experian Spain, and you will develop analytical solutions to the benefit of our clients and their customers. You will collect and analyze large datasets to uncover insights and create solutions that support organizational goals, in the field of credit life cycle, risk management, fraud modelling or marketing. Technical, analytical, and communication skills are needed to interpret data and influence decision-making.

Main responsibilities:

· Data Processing: Implementing processes to clean, transform, and organize raw data for analysis

· Optimization: Enhancing data delivery and automating manual processes to improve efficiency

· Data Analysis: Analyzing large volumes of structured and unstructured data to identify trends and patterns

· Data Visualization: Creating visual reports to clarify business pain points.

· Big data platforms: Using data/analytical platforms like Databricks, Cloudera, ...

· Statistical Techniques: Using statistical techniques to validate findings and ensure accuracy

· Machine Learning: Developing machine learning models and predictive algorithms to solve business problems

· Programming Skills: Applying programming languages and domain-specific tools for analysis

· Communication: Communicate with client and/or other departments/divisions within Experian to help ensure accurate and timely implementation of project work

· Solving problems: Identify potential problems in the end to end process and take ownership for the resolution

· 2–3 years of experience in statistical or analytical project work, and/or experience in the financial services, telecommunications, retail, technology, or consulting sectors.

· Degree or equivalent in a related field such as computer science, data science, statistics, mathematics, or information technology, physics.

· Highly PC literate with thorough knowledge of statistical:

· Strong proficiency in Python for data analysis, advanced analytics and automation: Python with Pandas, Numpy and Machine Learning Packages and IT packages. PySpark, TensorFlow or PyTorch is an a plus

· Knowledge of R, SQL, and SQL Server is highly valued as an additional asset

· Experience with cloud-based data platforms (e.g., Databricks, Cloudera, and Snowflake)

· knowledge of Power BI for creating interactive dashboards

· Understanding of statistical techniques which may be used to address client business issues

· An innovative and inquisitive mind, focused on addressing and solving data and analysis problems

· Fluency in written and spoken English

Good to have

· Knowledge or hands-on experience with Generative AI concepts, including LLMs, RAG, prompt engineering, and information retrieval.

Benefits/Perks:

• Great compensation package and bonus plan
• Core benefits including Private Health Care and Experian wellness program
• Flexible schedule, hybrid model of teleworking
• Flexible time off including volunteer time off, personal leaves and paid holidays

Proud to be a Worlds Best Workplace 2025

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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