Data Science Manager

We are seeking an experienced Data Science Manager to lead our data science teams at Salla. This role is pivotal in developing our roadmap for AI applications and services, ensuring that data-driven insights and models align with business objectives. The ideal candidate will oversee a team of data science professionals, including Data Science Team Leads and individual contributors, driving the planning, development, and deployment of advanced analytics and machine learning models.

Responsibilities

• Team Leadership: Manage and mentor a diverse team of data scientists, machine learning engineers, MLOps professionals, and business analysts. Foster a collaborative and innovative environment.

• Project Management: Lead the conception, planning, and execution of data science projects. Align these projects with organizational goals and ensure timely delivery.

• Data Analysis and Model Building: Oversee the analysis of raw data, including quality assessment, cleansing, preprocessing, and structuring for downstream processing. Supervise the development and implementation of machine learning models across various domains.

• Research and Development: Conduct R&D activities in data science and machine learning practices. Utilize deep learning techniques to solve complex problems in areas such as recommendation engines, chatbots, and natural language processing (NLP).

• Model Deployment: Collaborate with engineering and product teams to ensure seamless integration of AI models into production. Provide technical guidance and support during deployment.

• Innovation and Solution Design: Design and develop scalable machine learning models, ensuring accuracy and effectiveness. Create new service offerings and solutions in e-commerce and other fields.

• Cross-Functional Collaboration: Work closely with data engineers, quality assurance officers, business analysts, and software developers to translate ideas and prototypes into robust solutions.

• Continuous Learning: Stay abreast of the latest trends and advancements in data science, machine learning, and large language models (LLMs) to drive innovation within the team.

• Stakeholder Communication: Communicate complex data insights and model outcomes to stakeholders, ensuring clarity and alignment with business objectives.