The role of the Sr. Data Scientist is to work on business impact-driven AI and ML projects with an emphasis on predictive solutions. This role will require extensive experience using a variety of data mining/data analysis tools and methods, building and implementing machine learning models, using/creating algorithms, creating/running simulations, and deploying and monitoring solutions in production settings. The Senior Data Scientist must have a proven ability to drive business results with their data-based insights and must be comfortable working with a wide range of stakeholders and functional teams. The right candidate will have a passion for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes.

Job Responsibilities:

• Develop proof-of-concept (POC) data science solutions for business use-cases as specified by key stakeholders
• Specify data requirements to solve a given use case
• Analyze and visualize data to draw insights and validate hypotheses
• Identify the best approach / algorithms to solve a given use case
• Prototype algorithms using Python and/or other languages with appropriate libraries and frameworks
• Present solutions / findings to senior management
• Continuous research to stay updated with state-of-the-art artificial intelligence, machine learning, and data science tools & solutions
• Work with engineering teams to productize solutions

Skills & Qualifications:

• MS/PhD in Computer Science, Mathematics or related discipline (or equivalent experience)
• 3 – 8 years of data science, machine learning, deep learning, NLP experience
• Demonstrated experience deploying ML solutions at scale in a commercial setting
• Excellent communication skills – verbal, written and presentation
• Experience working with relational (i.e., SQL) and NoSQL (i.e., MongoDB, Cassandra, ElasticSearch) database technologies
• Experience in distributed analytic processing technologies a plus (e.g., Spark, Hadoop ecosystem technologies)
• Hands-on experience with one or more major cloud-based ML platforms: Azure / GCP / AWS.AWS experience preferred.
• Strong machine learning background including experience working with the following classes of algorithms:regression, classification, clustering, dimensionality reduction, sequence models, time series analysis, association rule mining, text mining (NLP), and ensembles.
• Deep understanding of model evaluation metrics like AUC, RMSE, log-loss, entropy and statistical concepts like P-value, T-test, F-test
• Demonstrable experience in Exploratory Data Analysis, Data Wrangling and Data Storytelling
• Python programming experience a must
• Familiarity with one or more common deep learning frameworks (Tensorflow, MXNet, Keras, PyTorch, etc.)
• Experience with common Python data analysis and machine learning frameworks (scikit-learn, xgboost, scipy, numpy, pandas)
• Comfortable working in Linux/Unix environments
• Familiarity with existing Machine Learning APIs (e.g., Microsoft Azure Machine Learning API, Amazon Machine Learning API, Google Prediction API, etc.) is a plus
• Familiarity with one or more high-performance programming languages (e.g., Java, C++, Scala) a plus
• Familiarity with code versioning tools and software testing frameworks and methodologies a plus