What You’ll Do: 

• Develop statistical/machine learning models by partnering with business leaders to design feasible and impactful data science solutions.  

• Develop and enhance the machine learning life cycle, adopt and implement governance policies for enterprise algorithms, develop knowledge-sharing content, and other endeavors related to our machine learning program.  

• Optimize model and data performance in terms of reduced computation time and cost.  

• Interpret outputs and regularly present findings to various levels of stakeholders and technical experts.  

• Monitor, maintain, optimize, and continuously improve deployed machine learning solutions during day-to-day operations.  

• Mentor data scientists and junior data scientists by providing guidance, advice, and support in various facets of advanced analytics. 

What You’ll Bring: 

• 5+ years of professional experience working as a Data Scientist or in a similar role, turning data into insights and impactful business outcomes.  

• Strong development experience with any of the following software languages: Python, R, SQL, or Scala.  

• Professional knowledge of Machine Learning Algorithms: NLP, Neural networks, deep learning, Naïve Bayes, regression, random forest, clustering, and text mining.  

• Strong experience with common ML libraries and frameworks (ex: PyTorch, Tensorflow, Scikit-Learn, MLflow, Sagemaker, Kubeflow, Spark MLlib, HuggingFace, or LangChain).  

• Proficiency with data platforms such as Databricks, Snowflake, BigQuery, Spark in any flavor, HIVE, Hadoop, Cloudera, or RedShift (we use Databricks).  

• Comfortable collaborating with software engineers, data engineers, and business leaders to understand business and technical challenges and drive towards complete resolutions with these cross functions.  

• Proven ability to communicate clearly and effectively to audiences of varying technical levels  ​
   

Pay Range: $143,000 – $195,000 Annually 

This hiring range is a reasonable estimate of the base pay range for this position at the time of posting.  Pay is based on a number of factors which may include job-related knowledge, skills, experience, business requirements, and geographic location.