Data Scientist

6 months ago

Vancouver, Canada E-Comm 9-1-1 Full time

WHO WE ARE

At E-Comm 9-1-1, we are committed to building a diverse and inclusive workforce that represents the many communities that we proudly serve

OUR VALUES
RESPECT | ACCOUNTABILITY | INTEGRITY | SERVICE | COLLABORATION

We are seeking an experienced **Senior Data Scientist **to join our growing Data & Analytics team. As a Senior Data Scientist, you will play a pivotal role in shaping our data strategy and driving actionable insights. For this newly created role, we are looking for someone who is passionate about leveraging data to solve complex problems and drive business success.

Reporting to the Executive Director, Data & Analytics, you will be responsible for using predictive modelling, statistics, machine learning (ML), data mining, and other data analysis techniques to find patterns and trends and uncover insights to help with predicting staffing and operational needs, future outcomes, mitigating risks and improving operational and strategic decision-making.

In this role, you will analyze structured and unstructured data, model complex problems, and identify opportunities for process and product optimization by using scientific methodologies, statistical, algorithmic, mining, and visual techniques. This role assists in developing ML predictive and prescriptive analytics models through the innovative understanding and use of large data sets and the verification of effectiveness to improve business processes and outcomes.

Key responsibilities in this role include:

- Serving as a functional lead for Data Science on complex projects with diverse scope, including primary contact for internal liaison between Data and Analytics team and project teams, operations, and other functional groups
- Understanding key business priorities and challenges to design the right actionable data science and analytics solution to address. Communicating analytic solutions to management and sharing AI product status throughout the various stages of the product lifecycle
- Designing, builds and implements data science and machine learning models to identify patterns, trends, and opportunities that can make predictions or reduce workload and increase system efficiency to make a significant impact across various domains within E-Comm. Ensure data compliance and security needs are met in system construction
- Developing improvements to operational workflows and support decision making by researching, developing, and evaluating models and algorithms that leverages tools such as process modeling, operations research, simulation, and optimization and applied machine learning
- Identifying, cleaning, and integrating large sets of structured and unstructured datasets from disparate sources for use in ML models and products. Enhancing data collection procedures to include information that is relevant for building advanced ML models
- Peer-reviewing code and mentoring and supporting junior team members
- Building strong partnerships with other teams internally and externally to solve problems, and ensure we deliver a cohesive customer experience
- Making recommendations to management regarding strategic actions to maintain the data pipelines, analytic architectures, and life cycle, to avoid potential negative consequences and system failures, and to increase the positive impacts of data analytics system

**WHAT YOU WILL BRING**:

- A level of education, training and experience equivalent to a Master’s Degree or PhD in Data science, Computer Science, Mathematics, Operations Research or other quantitative discipline
- A minimum of five (5) years’ experience in related data-specific roles
- Display comprehensive understanding of, and skills using, statistical and data mining techniques such as GLM/Regression, Random Forest, Boosting, Trees, text mining, network analysis, simulation, scenario analysis, and clustering analysis
- Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc
- Demonstrated ability to perform analytical functions and transform database structures including creating datasets and writing computer code to execute complex queries using statistical computer languages such as Python, R, and SQL
- Demonstrated proficiency working with large volumes of data across multiple servers using distributed data/computing tools such as Hadoop, Spark, MySQL, AWS, etc
- Demonstrated proficiency working with both relational (SQL) and non-relational databases (NoSQL)
- Demonstrated understanding of data privacy, security and related tools such as anonymization and encryption
- Demonstrated skills in using data visualization tools (such as Power BI, Tableau, Matplotlib, D3, ggplot) and to visually present complex data to stakeholders for consideration
- Strong analytical, critical thinking, and evaluation skills to discern and help solve the important problems facing E-Comm Operations, to identify new ways to leverage our data, and to direct efforts in the r

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