AI Analyst
4 weeks ago
At New Scientist - Jobboard, we're seeking a talented AI Analyst to join our team. As an AI Analyst, you'll play a crucial role in analyzing complex datasets and deriving meaningful insights using AI models. Your expertise in machine learning techniques, such as regression, classification, clustering, and natural language processing, will help us shape the future of our data-driven decision-making.
Key Responsibilities:
- Data Analysis and Interpretation: Analyze large datasets using machine learning techniques and AI tools to uncover trends, patterns, and insights that inform business decisions.
- Apply AI Models to Business Challenges: Work closely with data scientists and AI engineers to apply AI models to real-world business problems. You'll analyze model outputs, validate results, and ensure that AI-driven insights align with business objectives.
- Predictive and Prescriptive Analytics: Use AI tools to create predictive models that forecast future outcomes based on historical data. You'll help businesses make data-driven decisions by providing insights on future trends, risks, and opportunities through prescriptive analytics.
- Visualization and Reporting: Create compelling data visualizations and reports using tools like Tableau, Power BI, or Matplotlib to communicate AI-driven insights to stakeholders. You'll translate complex AI outputs into easy-to-understand, actionable recommendations.
- Collaborate with Cross-Functional Teams: Partner with product managers, marketing teams, and other business units to understand their data needs. You'll help translate business requirements into data-driven AI solutions and insights that support strategic decisions.
- Monitor and Validate AI Models: Continuously monitor the performance of AI models in production, ensuring their accuracy and relevance. You'll validate model outputs and work with data scientists to retrain or fine-tune models as needed to maintain high performance.
- Stay Updated on AI Trends: Stay current with the latest advancements in AI, machine learning, and data analysis.
Requirements:
- AI and Machine Learning Knowledge: Solid understanding of machine learning techniques such as regression, classification, clustering, and natural language processing (NLP). You're experienced in applying AI models to analyze large datasets.
- Data Analysis Expertise: Strong analytical skills with experience in data mining, statistical analysis, and AI-driven insights. You're proficient in Python, R, or SQL and comfortable working with tools like TensorFlow, Scikit-learn, and Pandas.
- Data Visualization and Reporting: Proficiency in data visualization tools like Tableau, Power BI, or Matplotlib. You can effectively communicate AI insights to non-technical stakeholders through compelling visualizations.
- Business Acumen: Ability to translate complex data into actionable business insights. You have a keen understanding of how data-driven strategies can impact key business decisions and objectives.
Education and Experience:
- Bachelor's or Master's degree: In Data Science, AI, Statistics, Business Analytics, or a related field. Equivalent experience in data analysis or AI-driven insights is also highly valued.
- Certifications or additional coursework: In AI, data analytics, or machine learning are a plus.
- Experience: 3+ years of experience in data analysis or AI analytics, with hands-on experience applying machine learning models to derive insights from large datasets.
What We Offer:
- Paid Time Off: Competitive vacation, sick leave, and 20 paid holidays per year.
- Work-Life Balance: Flexible work schedules and telecommuting options.
- Professional Development: Opportunities for training, certification reimbursement, and career advancement programs.
- Wellness Programs: Access to wellness programs, including gym memberships, health screenings, and mental health resources.
- Life and Disability Insurance: Life insurance and short-term/long-term disability coverage.
- Employee Assistance Program (EAP): li>
- Tuition Reimbursement: Financial assistance for continuing education and professional development.
- Community Engagement: Opportunities to participate in community service and volunteer activities.
- Recognition Programs: Employee recognition programs to celebrate achievements and milestones.
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