Data Scientist
6 days ago
- Develop innovative data models and algorithms to drive predictive insights and strategic business decisions.
- Identify trends and patterns within complex data sets to inform product development and customer experience strategies.
- Collaborate with cross-functional teams to integrate data science into all aspects of business operations and decision-making.
- Lead the implementation of machine learning and AI techniques to automate processes and enhance analytical capabilities.
- Communicate complex data findings in a clear and actionable manner to stakeholders at all levels of the organisation.
- Champion a data-driven culture, advocating for the importance of data insights in achieving organisational goals.
- Ensure the integrity and accuracy of data used for analysis, maintaining high standards of data quality and governance.
- Drive continuous improvement by staying abreast of industry trends and advancements in data science and analytics technologies.
- Product Teams: Work closely with product managers and developers to integrate data-driven features and enhancements into products.
- Marketing Department: Partner with marketing to refine customer segmentation, personalise campaigns, and measure their effectiveness.
- Sales Teams: Assist sales with lead scoring models and customer insights to optimise sales strategies and performance.
- Customer Success: Provide analytics support to customer success teams to improve customer retention and satisfaction.
- Operations: Collaborate with operations to streamline processes and identify efficiency gains through data analysis.
- Data Science Principles: Profound understanding of statistical analysis, predictive modelling, and machine learning algorithms.
- Programming Languages: Proficiency in languages such as Python, R, or Scala, and familiarity with SQL for database querying.
- Data Visualisation: Knowledge of data visualisation tools and techniques to present complex data insights clearly.
- Big Data Technologies: Familiarity with big data platforms like Hadoop, Spark, or Kafka.
- Domain Expertise: Awareness of the industry SafetyCulture operates in, including safety regulations and quality standards.
- Analytical Thinking: Ability to dissect complex data sets and extract meaningful insights.
- Problem-Solving: Strong problem-solving skills to address business challenges with data-driven solutions.
- Communication: Excellent verbal and written communication skills for articulating data findings to non-technical stakeholders.
- Collaboration: Ability to work effectively in cross-functional teams and with various stakeholders.
- Project Management: Skills in managing projects, setting timelines, and meeting deadlines.
- Curiosity: A strong desire to explore data for hidden patterns and opportunities.
- Attention to Detail: Meticulous attention to detail to ensure accuracy in data analysis and modelling.
- Adaptability: Flexibility to adapt to new tools, technologies, and changing business needs.
- Innovative Mindset: A creative approach to developing new analytical methods and solutions.
- Ethical Judgment: Commitment to ethical standards in handling and analysing data.
- Equity with high growth potential, and a competitive salary;
- Hybrid working, we encourage you to create the best work blend while working from your home and the local SafetyCulture office;
- Access to professional and personal training and development opportunities;
- Hackathons, Workshops, Lunch & Learns;
- We encourage involvement in the community, open source work, attending talks and events, and experimenting with new technologies.
- In-house Culinary Crew serving up daily breakfast, lunch and snacks;
- Barista coffee machine, craft beer on tap, boutique wines and a range of non-alcoholic beverages;
- Quarterly celebrations and team events;
- Table tennis, board games, books library, and pet-friendly office.
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