The Data Scientist plays a pivotal role in planning, executing, and delivering machine learning-based projects. The bulk of the work will be in machine learning (ML) modelling, management and problem analysis, data exploration and preparation, data collection and integration, operationalization.

The Data Scientist will be a key interface between the analytics team(s), the business unit(s) and various other departments, including as IT. The Data Scientist is also self-driven, curious and creative and may also support the related roles of data engineer, and also is expected to evangelize effective data management practices and promoting better understanding of data and analytics in the organization.

Key Responsibilities:

Machine Learning

• Apply various ML and advanced analytics techniques to perform classification or prediction tasks
• Integrate domain knowledge into the ML solution; for example, from an understanding of customer journey, marketing, sales, etc.
• Testing of ML models, such as cross-validation, A/B testing, bias and fairness

Problem Analysis and Project Management

• Guide and inspire the organization about the business potential and strategy of artificial intelligence
• Identify data-driven/ML business opportunities
• Collaborate across the business to understand IT and business constraints
• Prioritize, scope, and manage data science projects and the corresponding key performance indicators (KPIs) for success
• Define and communicate governance principles

Data Exploration and Preparation

• Apply statistical analysis and visualization techniques to various data, such as hierarchical clustering, T-distributed Stochastic Neighbor Embedding (t-SNE), principal components analysis (PCA)Machine Learning
• Generate hypotheses about the underlying mechanics of the business process
• Test hypotheses using various quantitative methods
• Display drive and curiosity to understand the business process to its core
• Network with domain experts to better understand the business mechanics that generated the data

Data Collection and Integration

• Understand new data sources and process pipelines and catalog/document them
• Acquire access to various databases and other sources systems such as SQL or graph databases
• Create data pipelines for more efficient and repeatable data science projects
• Work closely with data engineers to design and automate data ingestion and preparation steps

Operationalization

• Collaborate with data engineers and IT to evaluate and implement ML deployment options
• Integrate model performance management tools into the current business infrastructure
• Implement champion/challenger test (A/B tests) on production systems
• Continuously monitor execution and health of production ML models
• Establish best practices around ML production infrastructure

What you bring:

• Completion of a Bachelor’s or Master’s degree in data science, statistics, operations research, applied mathematics, computer science or a related quantitative field
• 5+ years of relevant project experience in successfully launching, planning, and executing data science projects.
• Experience in one or more of the following commercial/open-source data discovery/analysis platforms: KNIME, Microsoft AzureML, RStudio, Spark, RapidMiner, Alteryx, etc.
• Coding knowledge and experience in several languages: for example, R, Python/Jupyter, Java, Scala, C++, Excel, MATLAB, etc.
• Experience with distributed data/computing tools: MapReduce, Hadoop, Hive, Kafka, also MySQL, and so on
• Experience with popular database programming languages including SQL, PL/SQL, for relational databases and upcoming nonrelational databases such as NoSQL/Hadoop-oriented databases such as MongoDB, Cassandra, and others
• Working knowledge of agile methodologies and well-versed in applying DevOps/MLOps methods to the construction of ML and data science pipelines
• Project experience in applying ML and data science to business functions
• Excellent business acumen and interpersonal skills; able to work across business lines at a senior level to influence and effect change to achieve common goals.

What we offer:

• Competitive salary and bonus
• Benefits and Pension Plan
• Product Allowances & Safe Ride Home Program
• An organization that cares about Corporate Social Responsibility
• Tuition reimbursement
• Training & Development Programs
• An opportunity to learn about the world of wine

We are committed to establishing a qualified workforce that reflects the diverse population it serves and we encourage applications from all qualified individuals. We are also committed to preventing and removing barriers to employment for people with disabilities, and we invite you to inform us should you have any accessibility or accommodation needs.