Applied Machine Learning Scientist I (Traditional AI)

TD • Boston, MA

2d

About The Position

The Applied Machine Learning Scientist I is responsible for providing technical expertise on advance analytics and machine learning across a broad range of analytics functions including data and modelling frameworks, tools, technology, processes and procedures. This role has a contributing role in the development of AI/ML systems and provides actionable insights to solve business problems.

The Advanced Analytics (AA) team at TD Bank serves as a center of excellence (CoE), providing essential support to US lines of business with their advanced analytics requirements. This dedicated team specializes in creating and implementing sophisticated statistical and Machine Learning and Artificial Intelligence solutions to address a wide range of strategic business challenges across consumer, commercial, and shared services sectors within TD Bank. The AA team collaborates closely with key stakeholders to identify opportunities for leveraging data-driven insights and predictive models to drive informed decision-making and optimize business outcomes. By harnessing cutting-edge analytical tools and techniques, the team helps TD Bank stay ahead of the curve in a rapidly evolving financial landscape. Additionally, they play a vital role in fostering a culture of innovation and continuous improvement by staying abreast of emerging trends and technologies in the field of advanced analytics. Through their expertise and dedication, the AA team contributes significantly to TD Bank's competitive edge and overall success in the marketplace.

This role is mainly focused on "Traditional AI" (less emphasis on Gen-AI and LLM), developing and applying a broad set of evolving advanced statistical and AI/ML techniques to solve business problems. It includes gathering, analyzing, and modeling a wide range of data, applying mathematical models/techniques and tools, and utilizing software engineering best practices to develop and implement solutions. The successful candidate will design and develop leading-edge techniques and innovative solutions to solve a wide array of business problems and provide actionable insights to solve business problems.

Requirements

• Undergraduate degree required, advanced technical degree preferred (e.g., math, physics, engineering, finance or computer science)
• Graduate's degree preferred with either progressive project work experience
• Works autonomously and is accountable for sound knowledge in a given AI/ML area and of various AI/ML frameworks, tools, processes and procedures, as well as organization issues, best practices and business/organization standards
• Sound knowledge of applications, systems, innovation, design activities, best practices, business/organization standards
• Solves complex problems, takes new perspectives on existing solutions
• Independently performs tasks from end-to-end to deliver quality results and meet timelines
• May work under guidance of more senior roles

Nice To Haves

• Experience in predictive modelling using various ML/AI techniques, with a particular focus on tree-based models such as XGBoost.
• Formal training or substantive experience in a quantitative field such as Computer Science, Statistics, Mathematics, or relevant fields.
• In-depth knowledge of ML/AI algorithms and techniques, such as Gradient Boosting Method, NLP, modern deep Neural Networks, and time series forecasting.
• Full stack experience in data science product delivery, including data collection, aggregation, analysis, and visualization, development and testing, implementation, and monitoring.
• Proficiency in Python, PySpark, PyTorch, and SQL programming languages as well as object-oriented programming.
• Familiarity with version control software or platform such as Git, Bitbucket or Github.
• Strong analytical and problem-solving skills are required to interpret data and draw conclusions.
• Ability to work independently and collaboratively in a fast-paced, dynamic environment.
• Excellent written and verbal communications skills.
• Good time management and project management skills with minimal supervision.
• Experience with distributed computing and parallel processing on large data sets using Spark.
• Ability to research and implement Machine Learning algorithms from academic research papers.

Responsibilities

• Develop robust and reliable solutions leveraging advanced techniques, such as advanced statistics, machine learning and AI, NLP, geospatial analytics, storytelling & visualization, helping to solve strategic business challenges and enable insightful actions.
• Leverage a broad stack of technologies and platforms and packages— Python, Azure DataBricks, PySpark, PyTorch, and more — to reveal the insights hidden within huge volumes of numeric and textual data.
• Work closely with various stakeholders, to successfully move the project through all phases of the model lifecycle, from ideation and design through data gathering, training, evaluation, control and governance partners review and approval process, implementation, and ongoing monitoring and maintenance, with minimal supervision.
• Effectively communicate model design and results to senior leaders and business partners, articulate the business problems from a technical/quantitative definition and facilitate key strategic discussions and provide thought leadership.
• Provide expertise on mathematical concepts for the broader analytics team and inspire the adoption of advanced analytics and machine learning across the organization.
• Maintain full professional knowledge of techniques and developments in the field of Machine Learning and AI, and share knowledge with peers, business partners, and senior management.
• Maintain relationship with the team's strategic partners, such as business teams, AI2, and governance and control partners.

Benefits

• Our Total Rewards package reflects the investments we make in our colleagues to help them and their families achieve their financial, physical and mental well-being goals.
• Total Rewards at TD includes base salary and variable compensation/incentive awards (e.g., eligibility for cash and/or equity incentive awards, generally through participation in an incentive plan) and several other key plans such as health and well-being benefits, savings and retirement programs, paid time off (including Vacation PTO, Flex PTO, and Holiday PTO), banking benefits and discounts, career development, and reward and recognition.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Number of Employees: 5,001-10,000 employees