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Localytics: Data Scientist


Build the future of mobile with Localytics. Named among the top places to work by The Boston Globe, we're changing mobile marketing and analytics through predictive modeling and machine learning.



Localytics Company: Localytics
Location: Boston, MA
Web: www.localytics.com


Build the Future of Mobile With Localytics
The meteoric rise of mobile is the biggest shift in human communication since the dawn of the internet, and smart businesses know that apps are the best way to capture the potential of this opportunity and make the best use of this medium.

Localytics offers a powerful real-time, cloud-based app analytics and marketing platform. We're proud to help some of the world's most well-known brands like The New York Times, Microsoft, Salesforce and eBay create great mobile experiences for their customers. Come join us in our bold mission to radically change the way that brands communicate with their customers through this quickly growing new medium.

Named on of the top places to work in Massachusetts by The Boston Globe, we're a fun, hungry, smart group of people passionate about transforming the way consumers connect with their favorite products and services.

The Role
Localytics' Product team is looking for a Data Scientist to enable our customers to create better and more personalized mobile and web app experiences.

Your team will work closely with both product and engineering to ensure the accuracy and interpretability of productized insights, and scalability of supporting infrastructure. We are tackling cutting edge problems in data science not limited to large-scale data processing, predictive modeling of app user behavior, and the visual communication of unique insights.

Examples of questions you'll be answering:
  • What are good algorithms for predicting app user behavior? How should we measure algorithm performance?
  • When can parallelism make your algorithm run faster? Slower?
  • How should we treat missing values when processing data for a training set? What are the costs and benefits of different techniques?
  • When should we expect to suffer from overfitting / curse of dimensionality? How can we preempt and compensate for it?

 
Areas of Expertise:
  • Proven experience evangelizing ideas to non-technical stakeholders in a commercial setting.
  • Machine Learning: Practical experience with algorithms used to predict user behavior (churn, dormancy, purchase conversion, etc.) including: linear and logistic regression, clustering, recommender systems, decision trees and random forests, naive Bayes, and support vector machines.
  • Software Engineering: Proven ability to build web applications and APIs to go from research to production using a performant programming language (Scala, Java, Python, etc.). Experience with version control systems, primarily Git.
  • Computer Science: Understanding of principals including search, retrieval, concurrency, recursion, traversal, reduction, and matching. Must have ability to scale out algorithms and demonstrate understanding of the problems that arise when doing so. Practical experience with distributed frameworks (Hadoop/MapReduce and/or Spark).

 
Qualifications:
  • 2+ years Statistics / Machine Learning
  • 2+ years concurrent Software Development
  • If PhD/Masters with no work experience, please include link to portfolio.

 
_Contact_:
Apply online at www.localytics.com/company/localytics-jobs/

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