The Digital data science department is looking to build predictive solutions for their mobile application and online business operations to enhance user experience and optimize operational performance. They need to create custom solutions and data science models to gain insights into customer digital behavior, forecast trends, assess sentiment, and analyze data for actionable insights, with a potential focus on financial services and banking products.
Requirements
- Strong programming abilities in SQL, Python, R, or similar languages in data exploration, data preparation, modeling, prediction, simulation, and statistical analysis
- Ability to use data and cloud environments such as Azure, Databricks, AWS, or Hadoop
- Experience with machine learning techniques and tools to build a variety of models, including logistic regression, XGBoost, neural networks, NLP, and clustering
Responsibilities
- Collaborate with senior data scientists and leaders to design and implement predictive models and custom solutions that enhance our digital offerings.
- Write efficient code in Python and SQL to manipulate and analyze data.
- Design, develop, and evaluate basic/routine predictive models and algorithms with some complexity
- Utilize traditional and machine learning techniques and tools to build a variety of models, including but not limited to logistic regression, random forest, XGBoost, neural networks, NLP, k-means clustering, ARIMA, and prophet forecasting.
- Analyze and interpret results with some complexity
- Develop and code basic modeling programs, algorithms, and automated processes
- Use modeling and trend analysis to analyze data
Other
- 0-2 years of experience in data science, statistics, and data analytics
- Technical writing skills
- Strong communication and data storytelling presentation skills of technical material
- Ability to collaborate and build relationships
- Desired: Bachelor's degree in data science, statistics, mathematics, computers science, engineering, or degrees in similar quantitative fields
