Job Responsibility

• Display Leadership/Team Orientation – Work collaboratively to achieve organization’s success. Effectively uses position and interpersonal skills, mobilizes and inspires others to take action
• Willing and able to lead beyond area of expertise. Manage/Coordinate work of direct reports, including talent development and performance management.
• Coordinate with stakeholders within a specific business domain on use cases, including collaboration with IT and other corporate functions, markets and business groups.
• Perform code reviews, research, technical problem solving, solution architecture.
• Identify valuable data sources and automate collection processes
• Undertake preprocessing of structured and unstructured data
• Analyze large amounts of information to discover trends and patterns
• Build predictive models and machine-learning algorithms, Selecting features, building and optimizing classifiers using machine learning techniques
• Data mining using state-of-the-art methods
• Processing, cleansing, and verifying the integrity of data used for analysis
• Present information using data visualization techniques

 Qualifications

• Experience managing technical teams, preferably in Artifical Intelligence, Machine Learning, Data Science, and Analytics
• Experience in developing and deploying solutions at the edge and integrating with legacy systems, including hands-on MLOps experience
• Previous corporate or consulting experience in managing analytical projects in large cross-functional organizations such as retail, restaurant or food service, CPG, financial services, etc.
• Strong understanding of data warehousing principles and big data architecture; prior experience in partnering with IT to drive large data management initiatives
• Good applied statistics skills, such as distributions, statistical testing, regression, etc.
• Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc
• Knowledge of R, SQL and Python; familiarity with Scala, Java or C++ is an asset
• Experience with common data science toolkits, such as R, Weka, NumPy, MatLab, etc Excellence in at least one of these is highly desirable
• Proficiency in using query languages such as SQL, Hive, Pig
• Experience with NoSQL databases, such as MongoDB, Cassandra, HBase
• Experience using business intelligence tools (e.g. Tableau, Power BI) and data frameworks (e.g. Hadoop)