We are working alongside an internal start up working exclusively with a top-tier consultancy located in Istanbul, Turkey. Our clients are committed to data science innovation and staying ahead of the curve in a rapidly evolving industry where generative AI is becoming a key factor.
As the Interim Data Scientist, you will spearhead the data initiatives and collaborate with cross-functional teams to drive data-driven strategies. Your expertise will be essential in extracting insights, building predictive models, and identifying opportunities to enhance the financial products and services.
Requirements:
Turkish speaker
Living in Turkey
Data Science experience in Financial Services background (preferred)
Strong background in Statistics and Mathematics
Strong team and business communication skills – can walk through approach with technical clients or explain technical concepts to non-technical people
Experience with Git and modern software development workflows
Experience with containerisation technologies, such as Docker and working with CI/CD pipelines
Familiarity with agile ways of working (Scrum, Kanban, etc.)
Expert knowledge of Python programming and machine learning frameworks (Scikit-learn, TensorFlow, Keras, PyTorch, etc.)
Solid understanding of foundational machine learning concepts and algorithms
Experience with tools in distributed computing, GPU, cloud platforms and Big Data technologies (e.g. GCP, AWS, MS Azure, Hadoop, Spark)
Key Responsibilities:
Collaborate closely with business leaders to understand challenges and provide data-driven solutions.
Present and clearly communicate data findings and recommendations to senior management.
Conduct in-depth data analysis on large and complex datasets, identifying patterns, trends, and correlations to draw meaningful insights that support business objectives.
Develop and implement predictive models using machine learning algorithms to forecast trends, behaviour, and outcomes.
Create clear and concise data visualisations and dashboards to communicate complex findings clearly to stakeholders.
Ensure data quality and integrity by cleaning, preprocessing, and transforming data to remove errors and inconsistencies, making it suitable for analysis.
Collaborate with teams such as marketing, product, and finance, to understand their data needs and provide data-driven insights and solutions to address business challenges.
Present recommendations based on data analysis to support strategic decision-making, product development, and process improvements.
Design and analyse experiments and A/B tests to evaluate the impact of changes and innovations, contributing to evidence-based decision-making.
Work alongside data engineers to define data requirements and optimise data pipelines for efficient data processing and storage.
Evaluate model performance regularly and implement monitoring to ensure the accuracy and effectiveness of deployed models.
Preferred Qualifications:
Advanced Degree in a quantitative discipline such as Computer Science, Engineering, Physics, Statistics, Applied Mathematics, etc.
Previous experience leading data science projects and teams.
Familiarity with cloud-based data platforms and tools.
