Back
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Tier-1 brand, metro location, mid-level generalist data title with broad required skills increases competition.
Core data skills transfer across industries, though financial and digital-marketing specialization raises domain specificity.
Explicit 2–5 years plus mandatory Python/PySpark, SQL, Hadoop and ML skills make screening highly strict.
Work with large and complex internal and external data sets to evaluate and support business strategies, particularly in digital marketing and risk domains.
Identify, compile, document data requirements, perform data collection, cleaning, exploratory analysis, and apply statistical models and predictive machine learning techniques such as Decision Tree and Logistic Regression.
Use SQL, Python/Pyspark, and big data environments like Hadoop to analyze data and generate actionable insights with limited direct business impact beyond own team.
2+ years of relevant experience, preferably in financial domain or digital marketing/experience domain.
Proficient in Python, Pyspark, SQL, and experienced with big data technologies like Hadoop.
Bachelor’s or equivalent degree required.
Experience with statistical techniques, predictive modeling, and working knowledge of tools like Adobe, MS Excel, and PowerPoint.
Has quantitative analytics skills with experience in statistical modeling and machine learning applied to marketing or risk data.
Operates well in a matrix environment, able to collaborate across cross-functional teams and detail-oriented in data documentation and processes.
Brings a combination of data science skills, practical experience in handling large data sets, and familiarity with financial services or digital marketing analytics.