TikTak

TikTak is Turkey's youngest and fastest-growing car rental & sharing company.

We know the city is full of opportunity, full of excitement, full of life.

For this reason; We are highlighting TikTak as a solution resource in order not to miss a moment in this wide experience pool. We are the new generation transportation brand for the new generation of urban residents, and we are a reason for the city to be experienced to the fullest. TikTak is the shortest way to get from home to work, from campus to concert.

The city is bustling and lively, just like us. In this direction, our goal is to be an important part of daily mobility in city life.

Our goal is also about freedom, innovation, and dynamism. Our work environment is a dynamic environment that supports innovation, where everyone can contribute with their ideas.

We are looking for a Data Science Professional for our rapidly growing teams in this environment.

• Solving real-world business challenges using data from our app, vehicle telematics devices, and field operations.
• Developing optimization models for vehicle allocation and routing, considering real operational constraints and delivering actionable plans for field teams.
• Building time series forecasting models to predict demand across different time periods and locations, including sparse data and strong seasonality.
• Designing anomaly detection models to identify unusual patterns in streaming sensor and operational data, and determine which signals require alerts.
• Developing classification models for risk and propensity prediction using tabular data, as well as image classification.
• Collaborating with business teams to define problems, success metrics, and expected outcomes before model development.
• Building scalable models using Python and SQL on AWS infrastructure (Redshift, S3, Airflow, Kinesis, Druid).
• Partnering with data engineers to deploy models into production through Airflow jobs or services, ensuring continuous monitoring and reliability.
• Measuring model impact against baselines or control groups, tracking business KPIs, and continuously improving models after deployment.

• 3+ years of experience in Data Science or Machine Learning Engineering, with hands-on experience deploying and maintaining at least one production model.
• Bachelor's degree in Computer Science, Statistics, Industrial Engineering, or a related quantitative field.
• Strong proficiency in Python, SQL, and statistical methods.
• Solid experience in at least two of the following areas: optimization, time series forecasting, anomaly detection, and classification.
• Hands-on experience with classical machine learning techniques for tabular and time series data (e.g., gradient boosting), including time-based validation and data leakage prevention.
• Ability to translate business challenges into measurable data science solutions and demonstrate impact through financial outcomes or KPIs.
• Experience with AWS services (SageMaker, Lambda), Docker, and CI/CD is a plus.
• Familiarity with optimization solvers such as OR-Tools is a plus.
• Experience working with geospatial and real-time data technologies (H3, GPS, Kinesis, Druid) is a plus.
• Knowledge of computer vision applications, particularly vehicle damage detection and classification (e.g., scratches vs. dents), is a plus.
• Experience building solutions with LLMs and Generative AI (LLM APIs, RAG, agent workflows), especially for operational use cases, is a plus.
• Previous experience in car sharing, ride hailing, mobility, or logistics industries is a plus.