Senior Data Scientist

Summary

Join Apptopia, a high-growth startup, as a Senior Data Scientist and contribute to our team building data products and advancing existing ones using machine learning and advanced analytics. You will lead the improvement of core modeling efforts, develop user profiles, and apply data science methods to new finance-focused products. Responsibilities include designing and implementing machine learning algorithms, performing feature engineering, and collaborating with various teams. You will also create data validation frameworks, design APIs, and stay updated on the latest advancements in data science. This role requires strong proficiency in Python and data science libraries, experience with cloud platforms, and a proven track record in deploying models in production environments. The ideal candidate will have experience with financial data and a self-starter attitude.

Requirements

• At least 5+ years of experience in applied data science roles
• Advanced degree in Computer Science, Machine Learning, Operations Research, Statistics, Mathematics, Engineering or related quantitative field
• Strong proficiency in Python and popular data science libraries (NumPy, Pandas, scikit-learn, TensorFlow, etc.) with experience in distributed computing frameworks such as Spark
• Proven track record in applying Data science/ML for the end to end development and deployment of value adding business products
• Experience with cloud platforms (AWS preferred)
• Experience deploying models in production environments with proper monitoring, versioning, and performance optimization
• Self starter who enjoys a fast paced start up environment with a supportive, remote-first culture
• Comfort with ambiguity and going from "0 to 1"

Responsibilities

• You will be a data scientist on the Product team where you will work on both building new data products from the ground up and advancing our existing products through application of advanced modeling and machine learning methods
• Research, identify, and test ensemble methodologies to continuously improve accuracy and coverage in our models used for core app usage estimates
• Identify and develop valuable user profiles and segments for our customers using both supervised and unsupervised methods
• Leverage bias adjustment and anomaly detection methods as we improve signal and build models from various data sources
• Design, develop, and implement machine learning algorithms to advance a broad set of use cases including app usage trend forecasting, consumer behavior prediction,, stock price movement estimation, user segmentation
• Perform feature engineering & produce high quality, modular, reusable code that incorporates coding best practices
• Perform data exploration and statistical analysis to discover new signal in our current datasets, including digital user behavior patterns
• You will collaborate with product, research and engineering teams to identify valuable opportunities and the most feasible solutions
• You will create robust data validation frameworks and statistical testing procedures to ensure data quality and model reliability
• You will design APIs and data delivery systems that integrate seamlessly with existing infrastructure
• You will stay current with the latest advancements in data science and machine learning, bringing innovative ideas and best practices to the company

Preferred Qualifications

• Experience working with financial data and alternative datasets preferred
• Knowledge of financial markets, trading strategies, or quantitative finance concepts preferred
• Familiarity with click stream, app usage, and/or observational panel data preferred