Data Scientist

Overview of Role

As the ideal Data Scientist you are someone who can do a deep technical dive and communicate effectively with others. You love wrangling messy data into an elegant solution, and helping others understand the power of their data. This role is a chance to have a huge impact on how businesses operate and make decisions on a daily basis.

As the ideal AI/ML Engineer, you are someone who can do a deep technical dive and communicate effectively with others. You love wrangling messy data into an elegant solution, and helping others understand the power of their data. This role is a chance to have a huge impact on how businesses operate and make decisions on a daily basis.

Responsibilities:

• Dive deep into a wide range of data (tabular, text, image, etc.) to identify pain-points and deliver data-driven insights to our clients.
• Utilize analytical techniques to determine areas of opportunities to help meet business goals.
• Leverage GCP services to train and deploy off-the-shelf (Vertex AI/AutoML/BQML) or custom models to address a client s business problem.
• Be a thought leader for your team on projects and contribute to key practice initiatives.
• Act as subject matter expert on pre-sales calls and requests for proposals.
• Drive successful delivery of analytics solutions.
• Create reports and presentations that showcase the value of your solution to our clients.
• Work with other members of the AI/ML team to establish a center of excellence and create standard operating procedures, accelerators, and sales assets.

Qualifications:

• Bachelor s degree in Data Science, Computer Science or similar.
• 3-6+ years of experience with data science.
• Python (TensorFlow, Keras, SciKit-Learn, PyTorch), SQL, Shell Scripting experience.
• Data Engineering experience in Data Cleansing, ETL/ELT Pipelines, Vector DBs, Relational DBs, NoSQL DBs, Warehouses
• Generative AI experience in LLMs, Prompt Engineering, Tuning, RAG, LangChain
• Statistics & Modeling experience with Time-Series, Clustering, Regression, Classification, Recommendation Systems, Deep Learning, Ensemble Modeling, Reinforcement Learning, EDA, Data Visualization, Feature Engineering, Model Evaluation, Responsible AI
• MLOps experience with GIT, building CI/CD Pipelines, API Development, Docker, Deployment, Retraining Pipelines, Monitoring, Model Versioning.
• Google Cloud Experience in the following tools: Vertex AI, Document AI, Cloud Run, Cloud Functions, BigQuery, Pub/Sub, Cloud Storage.
• Kubernetes, Looker, Graph Data Science experience is a plus.
• Ability to communicate complex, technical processes to non-technical business stakeholders.
• Ability to track changing business requirements and deliver quality solutions both independently and with teams of varying skill sets.