Offer summary

Qualifications:

Advanced degree in a quantitative field such as Computer Science, Machine Learning, or Statistics., At least 5 years of experience in applied data science roles., Proficiency in Python and data science libraries like NumPy, Pandas, scikit-learn, TensorFlow., Experience deploying machine learning models in production environments, preferably on cloud platforms like AWS..

Key responsibilities:

Develop and improve data products using advanced modeling and machine learning techniques.

Lead efforts to enhance core modeling accuracy and coverage, including ensemble methods and user segmentation.

Design and implement machine learning algorithms for various use cases like trend forecasting and consumer behavior prediction.

Collaborate with cross-functional teams to identify opportunities, ensure data quality, and integrate data solutions.

Job description

About the Role

Apptopia is seeking a Senior Data Scientist to join our dynamic, data-driven team at a high-growth startup backed by powerhouse investors like Mark Cuban and ABS Capital. We specialize in providing actionable competitive intelligence to investment firms and financial institutions by estimating worldwide downloads, revenues, and active users for every mobile app. We also provide a unique, highly valued product with app user behavior insights. Our actionable app-store data and intuitive business intelligence tool help companies like Google, Facebook, and top hedge funds make smarter decisions.

As a Senior Data Scientist you will be tasked with applying machine learning modeling, advanced analytics, data mining, and critical thinking skills to increase product value.

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

● You will take part and in many cases lead the thought process in our ever-improving core modeling efforts:

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

● You will apply various data science methods as we bring new finance focused products to market:

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

Required Qualifications

● 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"

● 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

If you’ve read this far, we’re guessing you’re intrigued. Let’s chat — your next adventure might start here.

Required profile