Sr. Data Scientist
About The Position
Premium Guard, Inc. is seeking a Senior Data Scientist to design, develop, and deploy machine learning and artificial intelligence solutions that support business decision-making and operational excellence. The role combines predictive modeling, statistical analysis, data engineering, and business partnership to solve complex problems and deliver measurable value across the organization. The ideal candidate can build production-grade machine learning models, communicate findings to executive leadership, and collaborate with engineers, analysts, and business stakeholders. The Senior Data Scientist will lead analytical projects from ideation through deployment and business adoption, contribute to the organization's AI strategy and technical standards, and mentor junior data scientists and analysts. Within the first year, successful candidates are expected to deliver machine learning solutions with measurable business value, build trusted stakeholder relationships, improve analytical decision-making, and help develop a scalable data science capability.
Requirements
- Bachelor's degree in Data Science, Statistics, Computer Science, Engineering, Mathematics, Economics, Operations Research, or a related quantitative field.
- At least 5 years of professional experience in Data Science, Machine Learning, Applied AI, or Advanced Analytics.
- Strong proficiency in Python and SQL.
- Experience developing and deploying machine learning models in production environments.
- Deep understanding of statistical modeling, machine learning algorithms, and model evaluation techniques.
- Experience with cloud platforms such as AWS, Azure, or GCP.
- Experience with large-scale data processing technologies such as Spark, Databricks, or distributed computing frameworks.
- Strong communication and stakeholder management skills.
- Demonstrated ability to independently lead complex analytical initiatives.
Nice To Haves
- Ph.D. in a quantitative discipline.
- Experience with deep learning frameworks such as PyTorch or TensorFlow.
- Experience with NLP, LLMs, generative AI, and agent-based AI systems.
- Experience deploying APIs, machine learning services, or AI applications.
- Experience with supply chain, manufacturing, healthcare, financial services, or customer analytics.
- Experience with MLOps, CI/CD, model monitoring, and model governance frameworks.
- Published research, patents, conference presentations, or significant contributions to open-source projects.
- Experience with R.
- Familiarity with Scikit-Learn, PyTorch, TensorFlow, XGBoost, NLP, deep learning, time series forecasting, optimization, generative AI, and large language models.
- Familiarity with Databricks, Spark/PySpark, Azure, AWS, Delta Lake, SQL Server, PostgreSQL, Power BI, Tableau, Plotly, Matplotlib, and Seaborn.
Responsibilities
- Develop, validate, deploy, and monitor machine learning models supporting forecasting, optimization, customer intelligence, operational decisions, and business growth.
- Design and implement predictive models using supervised and unsupervised learning techniques.
- Perform feature engineering, model selection, hyperparameter tuning, and model performance evaluation.
- Establish model governance processes, including documentation, explainability, fairness assessments, and monitoring.
- Translate business challenges into analytical frameworks and data-driven solutions.
- Conduct exploratory analysis, statistical testing, forecasting, and causal analysis to identify actionable insights.
- Present analytical findings and recommendations to technical and non-technical audiences, including senior leadership.
- Create dashboards, analytical products, and decision-support tools to improve business performance.
- Partner with data engineers to design scalable data pipelines and feature stores.
- Work with large structured and unstructured datasets across cloud environments.
- Build and optimize data workflows using cloud technologies and distributed computing frameworks.
- Support data quality, governance, and reproducibility standards across analytics initiatives.
- Collaborate with Product, Operations, Finance, Supply Chain, Sales, and IT teams to identify opportunities for AI and advanced analytics.
- Mentor junior data scientists and analysts.
- Contribute to the organization's AI strategy, best practices, and technical standards roadmap.
- Lead analytical projects from ideation through deployment and business adoption.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
