Data Analytics/Scientist

About the Role

Key Responsibilities

• Use advanced analytical algorithms and technologies (e.g., machine learning, deep learning, artificial intelligence) to mine and analyze large data sets.
• Design and construct new processes for modeling data.
• Develop predictive models and leverage big data technology to create solutions that support business decisions.
• Collaborate with data and analytics professionals and teams to optimize, refine, and scale analysis into mature analytics solutions.
• Play an active role in advancing innovative data strategies to understand consumer trends and address business problems.
• Use data mining and extraction techniques to assess the feasibility of AI/ML solutions for improved data processing and usage.
• Conduct large-scale analysis to discover patterns and trends by combining different modules and algorithms.
• Provide recommendations and advice to business leaders to maintain market competitiveness.
• Develop prediction systems and machine learning algorithms, and investigate additional technologies for innovative data solutions.
• Work with product teams and partners to support data-driven decision making, business planning, and future roadmaps.
• Provide specialized consulting, analytical, and technical support.
• Exercise judgment to identify, diagnose, and solve problems within given rules.
• Work independently and handle non-routine situations.

Requirements

• Intermediate proficiency in mathematics, statistics, and operations research.
• Knowledge of deep learning and machine learning.
• Understanding of trust, bias, and ethics in data science.
• Creative and critical thinking skills.
• Advanced proficiency in big data, data visualization, computational thinking, programming, data wrangling, and data preprocessing.
• Strong verbal and written communication skills.
• Ability to collaborate and work effectively in teams.
• Analytical and problem-solving skills.
• Influence skills and data-driven decision-making capabilities.
• Typically 5-7 years of relevant experience and a post-secondary degree in a related field or equivalent education and experience.
• Deep knowledge and technical proficiency gained through extensive education and business experience.

Nice to Have

• Experience with developing and deploying predictive models and machine learning algorithms.
• Familiarity with AI/ML tools and additional data technologies.
• Experience working in a financial services environment.

Qualifications

• Post-secondary degree in a related field or an equivalent combination of education and experience.

Benefits & Perks

• Health insurance
• Tuition reimbursement
• Accident and life insurance
• Retirement savings plans
• Performance-based incentives and discretionary bonuses
• Other perks and rewards