The Applied AI Specialist will help shape the future of Securitas by creating algorithms, models, and insights to innovate and improve business operations, impacting how employees help make the world a safer place.
Requirements
- Strong proficiency in programming languages, particularly Python and SQL
- Solid experience with AI/ML libraries and tools, including scikit-learn, XGBoost, NLTK or SpaCy, transformer-based models (e.g., via Hugging Face), and OpenAI APIs
- Skilled in data analysis and data wrangling, with the ability to clean, transform, and interpret complex datasets
- Experience with PowerBI, Dash, or Streamlit is a plus
- 3–4 years of hands-on experience working in a data, statistical modelling or ML role
- Bachelor’s degree in a quantitative field (e.g., statistics, machine learning, mathematics, computer science, economics) preferred, or equivalent practical experience
Responsibilities
- Build and validate predictive models using machine learning algorithms to solve business problems and forecast outcomes (e.g., customer churn, sales trends).
- Clean, transform, and analyze large datasets to uncover patterns, trends, and actionable insights that drive strategic decisions.
- Communicate findings through visualizations and reports, translating complex technical results into clear, business-relevant insights for stakeholders.
- Design and develop rapid proofs of concept to generate insights, improve efficiency, build momentum, and gain stakeholder trust, emphasizing business impact over technical complexity.
- Translate business needs into AI/data science prototypes by understanding data generation processes and business operations.
- Work closely with a global team of AI developers and data scientists to leverage their expertise in scaling prototypes into production-ready solutions.
- Continuously learn and contribute to best practices in data science and AI deployment within a collaborative, cross-functional environment.
Other
- A consultative mindset is essential.
- Collaborate with stakeholders to understand challenges, co-develop solutions, and iteratively refine ideas.
- Your ability to translate business needs into data-driven prototypes and communicate findings clearly is just as important as your technical expertise.
- A strong understanding of business processes—or a willingness to learn— is key.
- Demonstrate a consultative mindset by engaging deeply with business processes and fostering stakeholder confidence in AI-driven approaches.
