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AI and Data Analitics Manager

  • Hybrid
    • Istanbul, İstanbul, Türkiye
  • Technology

Job description

Today our client trades with nearly 1300 stores in 60 countries, with the company’s philosophy that “Everyone Deserves to Dress Well” enabling people to enjoy accessible fashion through quality products at affordable prices.

Their Digital Transformation and IT Department has more than 850 employees specialized in different fields of many teams. We foster collaboration through Agile/Scrum methodologies, best practices, and guiding principles.

When you join the IT team, you'll be working hand-in-hand with experts focused on digital transformation, operational processes, and retail software processes.

 

This hybrid position requires 2 days to be present at the office ( 8 days in a month rule). The headquarters is in Esenler ( with shuttle service to all around Istanbul).

 

We are seeking an experienced and highly motivated Data Analytics and AI Manager to lead our data-driven initiatives and manage a team of analysts and AI specialists. This role is crucial in transforming our data assets into actionable insights, designing AI-driven solutions, and implementing MLOps and data governance practices that enhance organisational decision-making. This role will be directly responsible for overseeing a team of 5 talented data scientists.

The successful candidate will identify, establish, and operationalize machine learning infrastructures, data pipelines, standards, and flows related to MLOps and integrate the team into these systems, ensuring they support efficient, scalable AI and machine learning solutions. Key technologies include Airflow, Python, and PyTorch, and familiarity with computer vision, natural language processing (NLP), and vector databases (VectorDB) is highly advantageous.

Key Responsibilities:

  1. AI & Machine Learning Solutions:

    • Identify, establish, and operationalize machine learning infrastructures, data pipelines, standards, and flows related to MLOps.

    • Oversee the end-to-end machine learning lifecycle, including data preparation, model development, deployment, and monitoring.

    • Implement MLOps best practices for model versioning, continuous integration, and automation to streamline deployment.

    • Evaluate and integrate AI/ML tools and platforms that can enhance business capabilities.

    • Ensure models are maintained, retrained, and continuously improved for accuracy and relevance.

    • Lead the development and deployment of machine learning models and AI applications to solve business challenges.

  1. Data Analytics & Insights:

    • Oversee the collection, storage, and analysis of large datasets, ensuring high quality and accuracy.

    • Conduct exploratory data analysis to identify patterns, trends, and insights that support strategic planning.

  2. Data Governance & Compliance:

    • Establish and enforce data governance policies to ensure data quality, consistency, and security.

    • Facilitate compliance with data privacy regulations, security standards, and ethical AI practices.

    • Partner with IT and data engineering teams to set up and maintain data pipelines and infrastructure, ensuring data accessibility and integrity.

    • Develop documentation, data dictionaries, and guidelines to support data governance frameworks and maintain transparency.

  3. Project Management & Cross-Functional Collaboration:

    • Manage data analytics and AI projects, ensuring they are delivered on time and align with business goals.

    • Coordinate with other teams to ensure data and model compliance with established governance policies and standards.

    • Lead cross-functional efforts to identify, prioritize, and implement data solutions that support various departments' needs.

  4. Leadership & Strategy:

    • Develop and implement data analytics, AI, and MLOps strategies to support business objectives.

    • Lead, mentor, and manage the team, fostering a collaborative and innovative work environment.

    • Collaborate with stakeholders across departments to understand business needs and drive data-driven decision-making.

    • Stay updated on the latest trends and advancements in data analytics, MLOps, machine learning, and artificial intelligence.

Job requirements

Qualifications:

  • Education: Bachelor’s or higher degree in STEM (science, technology, engineering and mathematics) or a related field.

  • Experience:

    • 8+ years of experience in software, data or related fields.

    • 5+ years of experience in machine learning, data science, or AI

    • At least 2 years in a managerial or team lead role, ideally managing data scientists.

  • Technical Skills:

    • Strong hands on experience in Python and relevant libraries (numpy, pandas, sklearn, GBDT libraries, pytorch, tensorflow etc.).

    • Strong experience with MLOps practices and tools (e.g. Airflow, MLflow, Kubeflow...) to streamline machine learning workflows.

    • Experienced in some of the following ;  NLP, Computer vision, Recommendation, Timeseries & Forecasting, CRMand marketing use cases (Segmentation, Campaign targeting, CLV, Churn...)

    • Familiarity with cloud-based AI/ML platforms (e.g. Vertex AI, Azure ML Studio...).

  • Leadership Skills: Demonstrated experience in managing a team, fostering a collaborative environment, and leading cross-functional projects.

  • Communication: Excellent verbal and written communication skills, with the ability to convey complex ideas to non-technical stakeholders.

Nice-to-Have:

  • Experience in Google Analytics.

  • Background in agile project management methodologies.

  • Industry certifications in AI, data analytics, or data science.

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