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Job Overview
We are looking for a highly skilled Senior Data Scientist to join our team and take on a leadership role in developing and deploying machine learning models. The ideal candidate will have hands‑on experience in analyzing large datasets, developing advanced machine learning models, and leading a team of data scientists. You will work with cutting‑edge technologies, particularly Google Cloud Platform services like Vertex AI and BigQuery, to build end‑to‑end data solutions and deliver actionable insights. This is a 100% hands‑on role where you will play a critical role in driving business decisions through data science.
Key Responsibilities End‑to‑End Project Lifecycle
Business Problem Identification: Work with business stakeholders to define key business problems and translate them into data science projects.
Data Collection & Preprocessing: Collect, clean, and preprocess data for modeling purposes.
Model Development & Implementation: Design, develop, and implement machine learning models (forecasting, classification, optimization, etc.) using Vertex AI, BigQuery, and other Google Cloud Platform tools.
Collaboration: Collaborate closely with data engineers to design and optimize data pipelines, and with business stakeholders to ensure models meet business needs.
Data Analysis & Visualization
Analyze large datasets to identify key trends, patterns, and insights.
Create detailed data visualizations and reports to communicate findings to business stakeholders.
Model Deployment & Monitoring
Deploy machine learning models into production environments using Google Cloud Platform, ensuring they meet performance and business objectives.
Continuously monitor and fine‑tune models to ensure they remain effective over time.
Leadership & Team Guidance
Lead and mentor a team of data scientists, guiding them in technical decision‑making, best practices, and efficient workflows.
Provide regular feedback and monitor team performance to ensure high productivity.
Continuous Improvement
Stay up to date with the latest advancements in machine learning and AI technologies.
Implement best practices in model development, deployment, and monitoring while maintaining strong data governance standards.
Required Skills & Experience Technical Skills
Machine Learning & AI: Hands‑on experience in building and deploying machine learning models, including classification, regression, forecasting, and optimization.
Programming: Highly proficient in Python and SQL, with extensive experience using libraries such as scikit‑learn, TensorFlow, and PyTorch.
Google Cloud Platform Expertise: Extensive experience with Google Cloud Platform, particularly Vertex AI and BigQuery for developing and deploying models.
Model Lifecycle Management: Strong experience in MLOps and operationalizing models in production, including model deployment, monitoring, and versioning.
Data Pipelines: Experience designing and implementing end‑to‑end data pipelines, working closely with data engineering teams.
Machine Learning Foundations
Strong understanding of core machine learning principles and algorithms.
Familiarity with advanced architectures, such as Transformers, LLMs (Large Language Models), and experience with prompting and fine‑tuning LLMs.
Experience with vector databases, retrieval‑augmented generation (RAG), and other advanced machine learning techniques.
Leadership Experience
3+ years of experience in a technical or leadership role, leading data science or technical teams, and driving program execution.
Demonstrated ability to manage and mentor teams, fostering a collaborative and high‑performance environment.
Cloud & Data Governance
Familiarity with cloud platforms such as Google Cloud Platform, AWS, or Azure. Preference will be given to Google Cloud Platform and experience with Vertex AI.
Strong understanding of data security, compliance, and governance standards, and adherence to these practices in all aspects of model development and deployment.
Behavioral Skills
Analytical Thinking: Strong problem‑solving skills with the ability to dive into complex data challenges and provide actionable insights.
Collaboration & Communication: Excellent communication skills, with the ability to collaborate with various stakeholders and translate their needs into technical requirements.
Teamwork: A team player who can wear different hats as needed and actively contribute to team success.
Adaptability: Fast learner and adopter of new technologies and methodologies, with a willingness to grow in a fast‑paced environment.
Experience
8+ years of hands‑on experience in data science, with a proven track record of building and deploying machine learning models in real‑world, production environments.
Must have worked on 2–3 production‑level projects as a data scientist.
Proven impact on business outcomes, such as cost reduction, efficiency improvements, or enhanced business processes through data science initiatives.
Job Details
Seniority level: Mid‑Senior level
Employment type: Full‑time
Job function: Engineering and Information Technology
Industries: Software Development
Location: Austin, TX
Compensation: $120,000 – $280,000 (varies by experience and role)
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Austin, TX .
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Key Responsibilities End‑to‑End Project Lifecycle
Business Problem Identification: Work with business stakeholders to define key business problems and translate them into data science projects.
Data Collection & Preprocessing: Collect, clean, and preprocess data for modeling purposes.
Model Development & Implementation: Design, develop, and implement machine learning models (forecasting, classification, optimization, etc.) using Vertex AI, BigQuery, and other Google Cloud Platform tools.
Collaboration: Collaborate closely with data engineers to design and optimize data pipelines, and with business stakeholders to ensure models meet business needs.
Data Analysis & Visualization
Analyze large datasets to identify key trends, patterns, and insights.
Create detailed data visualizations and reports to communicate findings to business stakeholders.
Model Deployment & Monitoring
Deploy machine learning models into production environments using Google Cloud Platform, ensuring they meet performance and business objectives.
Continuously monitor and fine‑tune models to ensure they remain effective over time.
Leadership & Team Guidance
Lead and mentor a team of data scientists, guiding them in technical decision‑making, best practices, and efficient workflows.
Provide regular feedback and monitor team performance to ensure high productivity.
Continuous Improvement
Stay up to date with the latest advancements in machine learning and AI technologies.
Implement best practices in model development, deployment, and monitoring while maintaining strong data governance standards.
Required Skills & Experience Technical Skills
Machine Learning & AI: Hands‑on experience in building and deploying machine learning models, including classification, regression, forecasting, and optimization.
Programming: Highly proficient in Python and SQL, with extensive experience using libraries such as scikit‑learn, TensorFlow, and PyTorch.
Google Cloud Platform Expertise: Extensive experience with Google Cloud Platform, particularly Vertex AI and BigQuery for developing and deploying models.
Model Lifecycle Management: Strong experience in MLOps and operationalizing models in production, including model deployment, monitoring, and versioning.
Data Pipelines: Experience designing and implementing end‑to‑end data pipelines, working closely with data engineering teams.
Machine Learning Foundations
Strong understanding of core machine learning principles and algorithms.
Familiarity with advanced architectures, such as Transformers, LLMs (Large Language Models), and experience with prompting and fine‑tuning LLMs.
Experience with vector databases, retrieval‑augmented generation (RAG), and other advanced machine learning techniques.
Leadership Experience
3+ years of experience in a technical or leadership role, leading data science or technical teams, and driving program execution.
Demonstrated ability to manage and mentor teams, fostering a collaborative and high‑performance environment.
Cloud & Data Governance
Familiarity with cloud platforms such as Google Cloud Platform, AWS, or Azure. Preference will be given to Google Cloud Platform and experience with Vertex AI.
Strong understanding of data security, compliance, and governance standards, and adherence to these practices in all aspects of model development and deployment.
Behavioral Skills
Analytical Thinking: Strong problem‑solving skills with the ability to dive into complex data challenges and provide actionable insights.
Collaboration & Communication: Excellent communication skills, with the ability to collaborate with various stakeholders and translate their needs into technical requirements.
Teamwork: A team player who can wear different hats as needed and actively contribute to team success.
Adaptability: Fast learner and adopter of new technologies and methodologies, with a willingness to grow in a fast‑paced environment.
Experience
8+ years of hands‑on experience in data science, with a proven track record of building and deploying machine learning models in real‑world, production environments.
Must have worked on 2–3 production‑level projects as a data scientist.
Proven impact on business outcomes, such as cost reduction, efficiency improvements, or enhanced business processes through data science initiatives.
Job Details
Seniority level: Mid‑Senior level
Employment type: Full‑time
Job function: Engineering and Information Technology
Industries: Software Development
Location: Austin, TX
Compensation: $120,000 – $280,000 (varies by experience and role)
Additional Information Referrals increase your chances of interviewing at Jobs via Dice by 2x.
Get notified about new Senior Data Scientist jobs in
Austin, TX .
#J-18808-Ljbffr