Data Science & Machine Learning Engineer

Key Skills

Java Programming, Design, Python Programming, SQL, Azure, AWS, Machine learning techniques, Data science techniques, Data Modeling, Snowflake, R Programming, MLOps tools, Data Engineering, Data pipelines, VR/AR frameworks

Job Description

The Senior Associate, Data Science drives cross functional analytics projects from beginning to end, builds relationships with partner teams, frames and structures questions, collects and analyzes data, and summarizes key insights in support of decision making. S//he works with engineers to evangelize data best practices and implement analytics solutions.

• Provide the essential synthesis of deep knowledge of MLOps and cloud services with data science fundamentals to help our automation efforts.
• Drive cross functional projects from beginning to end to help automate the ML infrastructure for rapid model development and testing, connecting those models to a variety of model serving platforms including ranking and streaming systems.
• Work with our IT, data engineering and data science teams to expand our architecture to access data staged from multiple data sources and/or systems to build, deploy or publish machine learning models that run efficiently in cloud pipelines.
• Design and implement pipelines to provide real-time data quality and model performance monitoring for timely interventions and ongoing assessment.
• Design and implement model management systems to effectively implement MLOps for banking and financial models.
• Translates business queries into actionable and commercial insights leveraging unstructured data and statistically robust techniques.
• Drives cross functional analytics projects from beginning to end, builds relationships with partner teams, frames and structures questions, collects and analyzes data, and summarizes key insights in support of decision making.
• Works with engineers to evangelize data best practices and implement analytics solutions.
• Evaluation and discovery of alternative data vendors including ability to quantifiably validate external algorithms and apply insights to commercially driven use cases.
• Performs quantitative analysis, including alpha assessment, risk analysis, portfolio construction and return attribution to enhance investment strategies using sourced and external data.
• Collaborates across functional areas of our business at every level of seniority to uncover and address opportunities for scalability and growth.

Qualifications:

To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

Education:

• Bachelor's Degree or equivalent work experience in Statistics, Computer Science, Physical Sciences, Economics, or an equivalent technical field (required)
• Master's Degree in Statistics, Computer Science, Physical Sciences, Economics, or an equivalent quantitative field. (preferred)

Experience:

• 4+ years in Data mining/advanced analytics applied to large-scale data-intensive projects.

Skills:

• Minimum of 4+ years non-internship professional experience developing business problem related statistical/ML modeling with industry tools.
• Minimum of 4+ years of hand-on working experience with structured programming languages and modern machine learning libraries, frameworks, and technologies including Python or R, SQL, etc.
• Minimum 4+ years of experience working with cloud services/platforms, Google, Azure and/or AWS
• Experience with Snowflake/Databricks or similar platform. Working experience with model registry will be desirable.
• Ability to adapt to various programming languages and environments.
• Knowledge of the principles of machine earning, classification models, time series regression and stochastic statistics to deliver improved business performance.
• Demonstrated ability to communicate complex concepts.
• Strong quantitative and problem-solving skills with focus hypothesis formulation and testing.
• Individually motivated and possess sound judgment, integrity, and a solid work ethic.
• Ability to clearly communicate complex results to technical and non-technical audiences.
• Ability to utilize analytics in a collaborative manner across business functions and product lines to derive optimum solutions.
• Experience with banking/financial system is preferred