Lead Decision Scientist, Machine Learning Engineer, US 2024

Aimpoint Digital - Boston, MA

Full-time - Mid Level

Remote - Boston, MA

Professional, Scientific, and Technical Services

About the position

The Lead Decision Scientist at Aimpoint Digital is responsible for enabling clients to maximize the value of their data through machine learning and statistical modeling. This role involves working independently on client engagements, developing analytical solutions, and contributing to the growth of the decision sciences practice. The position requires collaboration with clients to design end-to-end solutions and involves coding, model deployment, and stakeholder management.

Responsibilities

• Become a trusted advisor working with clients to design end-to-end analytical solutions
• Work independently to solve complex data science use-cases across various industries
• Design and develop feature engineering pipelines, build ML & AI infrastructure, deploy models, and orchestrate advanced analytical insights
• Write code in SQL, Python, and Spark following software engineering best practices
• Collaborate with stakeholders and customers to ensure successful project delivery

Requirements

• Databricks experience is required
• Degree in Computer Science, Engineering, Mathematics, or equivalent experience
• Experience with building high quality Data Science models using Databricks ML to solve client's business problems
• Experience in deploying models via model serving within Databricks
• Experience with managing stakeholders and collaborating with customers
• Strong written and verbal communication skills required
• Ability to manage an individual workstream independently
• 3+ years of experience developing ML models in any platform (Azure, AWS, Google Cloud Platform, Databricks etc.)
• Ability to apply data science methodologies and principles to real life projects
• Expertise in software engineering concepts and best practices
• Self-starter with excellent communication skills, able to work independently, and lead projects, initiatives, and/or people
• Willingness to travel

Nice-to-haves

• Consulting Experience
• Databricks Machine Learning Associate or Machine Learning Professional Certification
• Familiarity with traditional machine learning tools such as Python, SKLearn, XGBoost, SparkML, etc.
• Experience with deep learning frameworks like TensorFlow or PyTorch
• Knowledge of ML model deployment options (e.g., Azure Functions, FastAPI, Kubernetes) for real-time and batch processing
• Experience with CI/CD pipelines (e.g., DevOps pipelines, Git actions)
• Knowledge of infrastructure as code (e.g., Terraform, ARM Template, Databricks Asset Bundles)
• Understanding of advanced machine learning techniques, including graph-based processing, computer vision, natural language processing, and simulation modeling
• Experience with generative AI and LLMs, such as LLamaIndex and LangChain
• Understanding of MLOps or LLMOps
• Familiarity with Agile methodologies, preferably Scrum