Role:Data Scientist Location:Los Angeles, CA

You Will

• Participating in activities across the data science lifecycle: business case definition, data collection, cleaning, integration, analysis, visualization, feature engineering, modeling with machine learning algorithms, interpreting the models/results, and reporting.
  
• Communicating and coordinating effectively with product managers, software engineers, analytical groups and customer-facing teams in an agile environment.
  
• Working with data processing pipelines for analyzing gigabyte- to terabyte-scale data from multiple sources.
  
• Designing actionable data products based on statistical analysis and machine learning methods and working on their deployment to enterprise systems to move the needle for business at client Insights.
  
• Learning continuously in the areas of data science, machine learning, ad technology, marketing operations, data ecosystems, content operations, social media analysis and industry standard measurements.

You Have

• Degree in computer science, engineering, statistics, or other quantitative fields. (Master??s degree is preferred)
  
• Solid understanding of popular machine learning algorithms including supervised, un-supervised, and semi-supervised ones. What is the difference between algorithms? What algorithm would you choose for a given problem and why? What are the pros and cons of these algorithms? What is cross validation, hold-out sample, RMSE, overfitting, bias, â?¦?
  
• Proficient in one or more core data science programming languages (Python or R) and the ability to become functional in emergent languages and APIs as needed (Java, Scala, â?¦).
  
• Practical experience of building a full cycle machine learning engine from cleansing data to training and hyper parameter optimization to methods for evaluating the accuracy to identifying the ways to improve the accuracy of the model.
  
• Exposed to and experienced with state-of-the-art machine learning toolkits such as Spark ML, TensorFlow, scikit-learn, xgboost, â?¦ preferably in Big Data frameworks (e.g. Apache Spark).
  
• A self-learner with capability to switch from the independent contributor and leader of the project to a collaborative contributor on the team (and vice versa) depending on the demand of the project and availability of the resources.
  
• Collaborate with stakeholders, partners and clients to ensure that all parties are aligned and supportive of the project's priorities, requirements, timeline and objectives.
  
• Familiarity with the MapReduce paradigm and Apache Spark project.
  
• Proficient with SQL as a means of gathering data from relational databases.
  
• Practiced data manipulation and mining of structured and unstructured data.
  
• Experience in visualizations for business stakeholders using a variety of visualization tools from MS Excel, libraries in R/Python.
  
• Familiarity with AWS ecosystem is a plus.