Manager - Analytics

JOB DESCRIPTION : 
As Data and Analytics manager, you will be responsible for managing the design, development, and implementation of Azure data engineering/visualization and data science solutions in GCPL with a specific focus on Media and Marketing. This role requires a blend of hands-on technical expertise, and strong business understanding. The responsibility also includes evaluation and implementation of emerging technologies in Azure data tech stack, data science, AI/ML and drive standardization and implementation of best practices.


Your Roles & Responsibilities

 End-to-End Project Development: Lead the conceptualization, development, and execution of data science projects across various functions and geographies within GCPL, ensuring  alignment with business objectives and strategies.
 Cross-functional Collaboration: Foster effective collaboration with internal stakeholders such as marketing, sales, supply chain, and finance to identify data-driven opportunities, address business challenges, and deliver actionable insights.
 Vendor Management: Engage with external vendors and partners to leverage specialized expertise, tools, and resources for advanced analytics projects, ensuring quality deliverables within established timelines and budgets.
 Performance Monitoring: Establish metrics and KPIs to assess the performance and impact of data science initiatives, tracking progress against goals and recommending adjustments as necessary to optimize outcomes.
 Continuous Improvement: Stay abreast of industry trends, emerging technologies, and best practices in data science, actively seeking opportunities to enhance the company's analytical capabilities and drive innovation.
 Team Management: Mentor junior data scientists, providing guidance on project execution, technical skills development, and career growth.

Position Requirements

Qualification & Experience:
 Educational Background: Bachelor's or Master's degree in a quantitative field such as Computer Science, Statistics, Mathematics, Economics, or related disciplines.
 Professional Experience: Minimum of 5-8 years of experience in data science, preferably within the FMCG industry or related sectors.

Skills Required:

Must have:
 Technical Proficiency: Proficient in programming languages such as Python, R, or SQL, with hands-on experience in statistical analysis, machine learning, data visualization, and predictive modeling techniques.
 Analytical Skills: Strong analytical and problem-solving skills, with the ability to interpret complex data sets, extract actionable insights, and translate findings into business recommendations.
 Communication Skills: Excellent verbal and written communication skills, with the ability to effectively convey technical concepts to non-technical stakeholders and influence decision-making at all levels of the organization.
 Business Acumen: Sound understanding of FMCG business dynamics, consumer behavior, market trends, and competitive landscape, coupled with a strategic mindset and commercial awareness.
 Adaptability: Proven ability to thrive in a fast-paced and dynamic environment, managing multiple priorities and stakeholders while maintaining a focus on delivering high-quality results.

Good to Have:
 Deep Learning Frameworks: Exposure to deep learning frameworks such as TensorFlow, PyTorch, or Keras, with application in areas like time-series forecasting.
 MLops Understanding: Familiarity with MLops (Machine Learning Operations) principles and practices, including model deployment, monitoring, versioning, and automation, to ensure scalability, reliability, and performance of machine learning models in production environments.
 Cloud for Machine Learning: Experience working with cloud platforms (AWS, GCP, or Azure), especially with ML services like SageMaker, Databricks or Azure ML Studio for scalable and
production-grade solutions.
 AI Productization: Experience in translating data science models into business products or dashboards embedded within operational processes.