Senior AI/ML and Data Scientist
This role combines advanced analytics and machine learning with visualization expertise to help stakeholders make informed decisions quickly and effectively.
Key Responsibilities Develop, train, and optimize predictive models using frameworks such as TensorFlow, PyTorch, or Scikit-learn. Perform data exploration, feature engineering, and model evaluation to solve business challenges (e.g., incident prioritization, operational forecasts).Implement best practices in MLOps, ensuring models are deployed, monitored, and continuously improved in production environments.
Building predictive models for incident prioritization and real-time analytics. Data Analysis & Visualization Design, build, and maintain dashboards and reports in tools like Power BI, Tableau, Grafana, or Qlik. Present complex findings in clear, visually compelling formats that resonate with both technical and non-technical audiences.
Apply UX/UI principles to ensure dashboards are user-friendly, visually attractive, and actionable. Collaborate with data engineering teams to set up data pipelines, ensuring datasets are accessible, clean, and secure. Integrate multiple data sources (structured/unstructured) to generate holistic insights.
Work with cloud platforms (AWS, Azure, GCP) and containerized services (Docker, Kubernetes) as needed. Collaboration & Stakeholder Engagement Partner with cross-functional teams (product owners, business analysts, and IT) to translate business requirements into ML solutions and data visualizations.Communicate insights, model outputs, and visualization best practices effectively to a variety of stakeholders.
Contribute to building a data-driven culture by championing AI and analytics initiatives across the organization. Keep current with advancements in AI/ML, data visualization, and business intelligence techniques. Evaluate emerging tools and technologies to enhance predictive accuracy, dashboard responsiveness, and overall user experience.
Provide mentoring or training to team members on analytics, ML, and visualization best practices. Required Qualifications Education: Bachelor’s degree or higher in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field.Machine Learning Expertise: 3+ years of hands-on experience developing and deploying ML models in production (regression, classification, clustering, deep learning, etc.).
Programming Skills: Proficiency in Python or R for data analysis and model development. Familiarity with SQL for data querying. Data Visualization Tools: Proven track record creating dashboards in Power BI, Tableau, Grafana, or Qlik.
Analytical Mindset: Strong background in statistics, data wrangling, and problem-solving. Communication: Excellent written and verbal communication skills, with the ability to simplify and present complex data to non-technical audiences. Preferred Qualifications Cybersecurity Awareness: Previous experience or familiarity with cybersecurity best practices, particularly as they relate to AI model integrity and data privacy.
Advanced Credentials: Certifications in AI/ML (e.g., AWS ML Specialty, Google Data Engineer, Azure Data Scientist Associate). Cloud & DevOps: Experience with MLOps, containerization (Docker), orchestration (Kubernetes), and CI/CD pipelines. Domain Experience: Prior exposure to incident prioritization, operational efficiency, or business process automation use cases.
UX/UI Principles: Familiarity with user-centered design approaches to enhance dashboard engagement and usability. Collaboration Tools: Comfortable with Git-based workflows, Agile project methodologies, and ticketing systems. Requirements
Please refer to job description. Data Analysis Statistical Modeling Data Visualization SQL Business Intelligence Problem Solving Data Mining Critical Thinking Communication #J-18808-Ljbffr