Position Summary:

The Data Scientist will contribute to the design, development, and deployment of advanced data science and engineering solutions. This role bridges data science and engineering to enable scalable, high-performance analytics products and ad-hoc analyses that leverage data for actionable insights. The Data Scientist will collaborate with data engineering, product, analytics, and compliance teams to build robust data pipelines, deploy machine learning models, and develop solutions that power predictive analytics. This hands-on role is ideal for someone who combines strong technical expertise with a passion for operationalizing data science models at scale and delivering impactful insights to internal stakeholders.

Primary Accountabilities:

• Contribute to the design and deployment of machine learning models and advanced analytics pipelines to deliver scalable solutions.
• Collaborate with internal stakeholders on the design of machine learning models and advanced analytics to deliver a range of ad-hoc solutions, with the ability to identify commonalities in requests and propose new products based on recurring themes.
• Collaborate with data engineering teams, analytics counterparts, and internal stakeholders to design and implement robust, automated data pipelines that ensure data integrity, security, and performance. Help build modular, reusable components for data transformation, feature extraction, and model deployment using modern cloud technologies (e.g., GCP, AWS).
• Leverage real-time data streaming and big data processing tools (e.g., Spark, Kafka) to support analytics products and services.
• Work closely with engineering, analytics, and product teams to ensure seamless integration of data science models into customer-facing applications and internal platforms.
• Partner with compliance and security teams to ensure that all data workflows and analytics models adhere to regulations.
• Contribute to platform architecture discussions to align data science initiatives with broader technical and business objectives.

Required Qualifications:

• Bachelors Computer Science, Data Science, Mathematics, or related field required.
• Masters Computer Science, Data Science, Mathematics, or related field required.
• Doctorate Computer Science, Data Science, or related field preferred.
• 2-3 years in data science or machine learning, with familiarity in operationalizing models in production required.
• Proven programming skills in R/Python, SQL, and frameworks like TensorFlow, PyTorch, or Scikit-learn. (High proficiency).
• Proven ability to design and implement data pipelines using big data tools (e.g., Spark, Hadoop) and cloud platforms (e.g., GCP, AWS). (High proficiency)
• Experience deploying machine learning models via APIs or containerized frameworks like Docker and Kubernetes.