About the position
The Data Scientist I at TD Bank is responsible for providing technical expertise across a broad range of data analysis functions, including data modeling, visualization, data profiling, data origin and lineage, report design, and other specialized data management functions. This role requires the individual to work autonomously and be accountable for acting as a lead within a specialized business management function, providing strategic work direction to others. The Data Scientist I will leverage seasoned specialized knowledge to offer advice and guidance to various stakeholders and team members, inspiring the adoption of advanced analytics and data science across the organization. In this position, the Data Scientist I will create and build final datasets from external and internal datamarts for modeling and ad-hoc analysis, ensuring the data is clean and verifying its integrity. The role involves applying data mining techniques, such as supervised and unsupervised learning, to uncover meaningful patterns in the data. The individual will utilize statistical, econometric, and machine learning techniques on large datasets to measure results, identify causal impacts, and model future performance of products, customers, and campaigns. Additionally, the Data Scientist I will write, create, and interpret complex queries using SQL, HIVE, R, SAS, Python, and Spark for both standard and ad-hoc data analysis purposes. Collaboration is key in this role, as the Data Scientist I will work closely with cross-functional business partners and internal analytics team members to identify gaps and business problems. The individual will lead the design, development, and implementation of advanced models, creating meaningful presentations and analyses that communicate analytical insights effectively. The scope of this role may have enterprise-wide impact, focusing on short to medium-term issues (e.g., 6-12 months) and undertaking a variety of complex projects requiring specialist knowledge and integration of cross-functional processes. The Data Scientist I will oversee and independently perform tasks from end to end for supported lines of business or business units.
Responsibilities
- Provide technical expertise across a broad range of data analysis functions including data modeling, visualization, and report design.
- Work autonomously and act as a lead within a specialized business management function.
- Provide strategic work direction to others and offer specialized knowledge and guidance to stakeholders.
- Create and build final datasets from external and internal datamarts for modeling and ad-hoc analysis.
- Ensure data integrity and apply data mining techniques to uncover meaningful patterns in the data.
- Utilize statistical, econometric, and machine learning techniques on large datasets to measure results and model future performance.
- Write and interpret complex queries for data analysis purposes using SQL, HIVE, R, SAS, Python, and Spark.
- Collaborate with cross-functional business partners to identify gaps and business problems.
- Lead the design, development, and implementation of advanced models and create meaningful presentations of analytical insights.
- Synthesize data and analytical methods into actionable business strategies and communicate findings to business partners and executive management.
Requirements
- Bachelor's degree in Statistics, Operational Research, Applied Math, Engineering, or Science (Master's Degree Preferred).
- 5+ years of relevant experience in data science or analytics.
- Proficient PC skills including strong competency in MS Excel and PowerPoint.
- Working experience with machine learning tools and technologies such as Hadoop in big data and advanced analytics.
- Strong analytical and problem-solving skills to interpret data and draw conclusions.
- Excellent written and verbal communication skills.
Nice-to-haves
- Experience with advanced analytics and data science methodologies.
- Familiarity with financial services or banking industry data.
- Knowledge of data visualization tools and techniques.
Benefits
- Health insurance
- Paid time off
- Career development opportunities
- Training and onboarding sessions
- Competitive benefits plan
