Data Scientist
Indexed description
You know our users better than anyone - because you let the data do the talking. You spot patterns, surface insights and bring clarity to complex problems. Working closely with Product Owners and cross-functional teams, you help turn data into decisions, and decisions into impact. You don't just analyse — you own the problem end-to-end, from discovery all the way to deployment and beyond.
What a Data Scientist does in Titansoft
- Own the full data science lifecycle - from problem identification and framing, through analysis, model building, simulation and deployment, to performance monitoring and iteration.
- Partner closely with Product Owners and cross-functional teams to understand business challenges, translate them into data problems and drive solutions that improve our products.
- Design, run and analyse experiments including A/B tests and hypothesis testing, to evaluate product ideas and measure the real-world impact of your work.
- Apply statistical and machine learning techniques to build models for user segmentation, anomaly detection, prediction and optimisation.
- Handle and interrogate large datasets, uncovering patterns, trends and actionable insights that others might miss.
- Develop and maintain dashboards and analytical reports to support ongoing product monitoring and decision-making.
- Communicate your findings clearly and confidently to both technical and non-technical audiences, and contribute meaningfully to team discussions.
- Bachelor's degree in Mathematics, Statistics, Computer Science, Data Science, Information Technology or a related discipline
- Proficiency in Python and SQL, with experience with BigQuery or other cloud data platforms (e.g. Google Cloud Platform)
- Solid foundation in statistics experimental design, and data visualisation tools (Tableau preferred)
- Comfortable using AI tools (e.g. LLMs, AI assistants) to accelerate analysis, code and problem-solving
- Strong analytical thinking — you ask sharp questions and know how to find the answers in data
- Comfortable with ambiguity and evolving priorities
- Curious and self-driven — you embrace new tools, including AI, and evolve with the times
- Strong communicator — you can explain your work clearly to engineers, Product Owners and business leaders alike
- Prior experience (including internships or academic projects) that demonstrates end-to-end ownership — from problem scoping to model deployment and monitoring
- Familiarity with ML frameworks and experimentation pipelines
- A track record of turning data into a clear recommendation, not just a chart
- Experience building AI agents or automations that put data science to work in practical, scalable ways
- 18 days of rest and relaxation for each year (P.S. It gets even better over the years!)
- Competitive salaries and bonuses bench-marked against big players in the industry (Yeap, those companies!)
- Flexible working hours (Sleep in a little longer after fixing that pesky bug from last night)
- Comprehensive insurance coverage Very well-stocked pantry (We've never heard of the term 'Hunger Games', nope)
- Communities of Practice and Workshops catered for your growth and learning
- Substantial subsidies and programs to keep that creative flow while having fun (Health promotion program, annual overseas company outing, an annual dinner that nobody will ever forget, etc.)
- Hardcore work and hardcore fun!
Create a free Caio profile to unlock more results and save your role and location preferences.
Unlock free search