We are looking for a Senior AI/ML and Data Scientist, specializing in Predictive Modeling & Data Visualization, to build predictive models, design intuitive dashboards, and create meaningful data-driven insights. This role combines advanced analytics and machine learning with visualization expertise to help stakeholders make informed decisions quickly and effectively.

Key Responsibilities

1. Machine Learning & AI

• 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.

2. 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.

3. Data Handling & Infrastructure

• 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.

4. 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.

5. Continuous Improvement & Innovation

• 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

Please refer to job description.