Principal Data Scientist - Bigabid
New York, NY
About the Job
Bigabid is at the forefront of harnessing the power of data for mobile app growth. Built by a team of dedicated data scientists and engineers, our proprietary ad platforms, driven by machine learning, deliver unmatched results in the industry. We're proud to serve a rapidly expanding clientele of major app developers with cutting-edge programmatic user acquisition and retargeting technologies. Through our technology, we sift through tens of TB of raw data daily to make real-time ad recommendations.
We're seeking a Principal Data Scientist to enhance product performance and cost-effectiveness by leveraging expertise in ML and infrastructure systems. This role involves delivering data-driven insights and scientific solutions, exploring new vertical landscapes, and harnessing the extensive data resources available at Bigabid for deeper understanding.
At Bigabid, talent never goes unnoticed. We foster a collaborative environment where each individual is encouraged to grow and contribute to our shared success. While we push boundaries and redefine standards, we always remember to have fun.
Responsibilities:
- Lead the research and productization focused on understanding clients from new and emerging verticals.
- Deliver end-to-end ML products - from data QA to research, model development, prototyping, offline validation, production implementation, and online testing.
- Develop ML solutions using advanced techniques, specially tailored for new business landscapes.
- Creating a solid experiment design and metric framework to deliver trustworthy and impartial insights vital for guiding product and business decisions with reliability.
- Utilize the scientific method in designing, creating, tuning, and interpreting machine learning models tailored for these verticals.
- Write production-quality code using Python.
- Perform data manipulation, validation, and cross-vertical research.
- Innovate with fresh research ideas and insights that can provide value to clients from diverse verticals.
- Collaborate closely with our product and data engineering teams to identify trends, solve problems, and discover opportunities.
Excerpt:
Lead end-to-end ML product deliveries, tailored solutions for diverse landscapes, and collaborating across teams to innovate and solve challenges in a vibrant work culture
Requirements:
- 6+ years of experience in one or more of the following: Data Analysis and Exploration, statistical modeling, creating dashboards or reports, especially in the context of researching new business verticals or client segments.
- 4+ years of experience as a Data Scientist
- Proficiency in various machine learning techniques (e.g. DNN, random forest, gradient boosted trees, k-means clustering, XGBoost, Embeddings)
- Familiarity with tools commonly used in ML practices (e.g. TensorFlow, Keras, Scikit-learn, Pandas, Jupyter Notebook)
- Proficient scripting and programming skills in Python.
- Proficiency in experimental design, hypothesis testing, and diverse statistical analysis techniques like regression or linear models is a prerequisite, requiring robust knowledge and hands-on experience.
- Strong problem-solving abilities, adept at articulating product inquiries, extracting insights from large datasets, and using statistics to make informed recommendations
- Demonstrated capacity to take full ownership of projects from start to finish, showcasing initiative and creativity beyond mere task completion.
- Exhibited leadership and self-driven initiative, coupled with a willingness to both mentor others and embrace novel learning methodologies.