Data Scientist I

Work Location:

United States of America

Hours:

40

Pay Details:

$76,128 - $124,800 USD

TD is committed to providing fair and equitable compensation opportunities to all colleagues. The included salary range for this role takes into account multiple factors that are considered in making compensation decisions. The base pay actually offered may vary based upon candidate's skills and experience, job-related knowledge, licensure and certifications, geographic location, and other specific business and organizational needs. As TD puts career development at the forefront of our colleague experience, it is not typical for an individual to be hired at or near the top of the range for their role.

As a candidate, you are encouraged to ask compensation related questions and have an open dialogue with your recruiter who can provide you more specific details for this role.

Line of Business:

Data & Analytics

Job Description:

The Data Scientist I provides 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.

Depth & Scope:

• Works autonomously and accountable for acting as a lead within a specialized business management function and provide strategic work direction to others
• Provides seasoned specialized knowledge, advice and/or guidance to various stakeholders and team members
• Provides expertise on mathematical concepts for the broader applied analytics team and inspire the adoption of advanced analytics and data science across the organization
• Creates and builds final dataset from external and internal datamarts for modeling and adhoc analysis ensuring the data is clean  and verifies the integrity of the data
• Applies data mining techniques such as supervised and unsupervised learning to understand the meaningful patterns in the data.
• Uses statistical, econometrics and machine learning techniques on large dataset to measure results and show key trends in the data, identify casual impact and attribution, model and predict future performance of products, customers and campaigns
• Writes, creates and interprets complex queries (SQL, HIVE, R, SAS, Python Spark etc.) for standard as well as ad hoc data analysis purpose
• Collaborates and works closely with cross functional business partners, internal analytics team members to identify gap and business problems
• Leads the designs, development and implementation of Advanced models (Marketing stages, Attrition, Customer Value, media mix, digital attribution) and create meaningful presentations and analyses that tells a story focused on analytical insights
• Synthesizes data and analytical methods into actionable business strategy and communicate findings to business partners and executive management team
• Scopes of role may have enterprise impact
• Focuses on short to medium - term issues (e.g. 6-12 months)
• Undertakes and completes a variety of complex projects and initiatives requiring specialist knowledge and/or the integration of cross functional processes within own area of expertise
• Oversees and/or independently performs tasks from end to end for supported LOB or business units

Education & Experience:

• Bachelor's degree  in Statistics, Operational Research, Applied Math, Engineering and or Science (Master's Degree Preferred)
• 5+ years relevant experience
• Proficient PC skills including a strong competency in MS Excel and PowerPoint, and a variety of PC based analytical and reporting software packages
• Working experience in the knowledge, utilization and adoption of the latest tools (i.e. machine learning) and technologies (i.e. Hadoop) in big data and advanced analytics
• Strong analytical and program solving skills are required to interpret data and draw conclusions
• Excellent written and verbal communications skills

Customer Accountabilities:

• Provides expertise on mathematical concepts for the broader applied analytics team and inspire the adoption of advanced analytics and data science across the organization
• Interprets the meaning of new strategic directions and set objectives and measurements
• Implements monitoring and feedback systems to evaluate progress and identify ways of making continuous improvements
• Gathers and analyzes infor