Lead Data Scientist, Machine Learning Engineer

Summary

Join Aimpoint Digital, a leading analytics consulting firm, as a Lead Data Scientist. You will work independently on client engagements, designing and developing end-to-end analytical solutions using machine learning, AI, and statistical modeling. Responsibilities include collaborating with clients, building ML infrastructure, deploying models, and writing efficient code in SQL, Python, and Spark. You will need a degree in a relevant field and 3+ years of experience developing and deploying ML models. The role requires strong communication and problem-solving skills, and the ability to manage individual workstreams. Aimpoint Digital offers a full-time, remote work opportunity within the US.

Requirements

• Degree in Computer Science, Engineering, Mathematics, or equivalent experience
• Experience with building high quality Data Science models to solve a client's business problems
• Experience with managing stakeholders and collaborating with customers
• Strong written and verbal communication skills
• Ability to manage an individual workstream independently
• 3+ years of experience developing and deploying ML models in any platform (Azure, AWS, GCP, 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

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

Preferred Qualifications

• 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

Benefits

Full-time, remote work within the US