Recruiter at Landmark Online
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Lifestyle International - Lead Applied Scientist - Analytics (7-10 yrs)
Know us a little better!
- Landmark Group began its journey in 1973 with one store in Bahrain and has grown into one of the largest Retail and Hospitality conglomerates in the Middle East, Africa, and India. Currently the Group employs 55,000 employees, operates over 2,300 outlets, encompassing over 30 million square feet across 22 countries. Since 1973, the Group has created great brands that are market leaders, built strong partnerships and delivered exceptional value to customers.
- The Landmark Group is one of the leading Retail and Hospitality organizations in the Middle East and India. Its vast portfolio of successful businesses includes award-winning household brands like Baby shop, Lifestyle, Max, Splash and Home Centre.
- Culturally we are an open organization with open door culture and with Lean Structure. As an organization, we are ranked as a Great place to work and we are proud of our company values.
DLL - Data Labs @ LMG Introduction:
Data Labs at Landmark was established in 2015 as a strategic business function to innovate data driven solutions and to operate as advisors to CEOs and heads of functions. We have observed immense growth in the last 5 years expanding to a 100+ team across Dubai & Bangalore. The team follows an on-shore/off-shore model of delivery for Middle East and India business and consists of people with expertise in Retail Analytics, Product Development, solving problems across (not limited to) Loyalty Management, Inventory Management, Assortment Planning, End to End Supply Chain, Pricing, etc.
Job Title: Lead Applied Scientist / Applied Science Manager
Who are we looking for:
- Bachelor's or Master's degree in Computer Science, Mathematics, Statistics, Econometrics or Physics
- At least 7+ years of experience in a Data Science related field
- At least one year of experience in people management role
- Strong hands-on experience in Machine Learning and Statistics focusing on structured and unstructured data problems is a must
- Prior experience in working with large data sets, with big data processing tools like Spark. Must possess data engineering skills to do pre-processing, cleaning, and transformations
- Practical experience in some of the following areas: Customer Churn, Customer lifetime value estimation, Product Recommendation, Ecommerce Analytics, Market Mix Modelling, Inventory Management, Supply Chain Optimization, Price Optimization etc.
- Excellent programming skills preferably in Python or Pyspark and SQL
- Understanding of deploying machine learning models on cloud services (Azure, AWS, GC etc.) will be an added advantage
- Advanced engineering abilities to deliver flexible and scalable end-to-end machine learning solutions
- Excellent written and verbal communication skills, confidence in presenting ideas and findings to stakeholders, and ability to do so at the right level of detail
- Strong sense of urgency and commitments. Candidate should be passionate about driving change and influence across organization
- Open to travel on need basis (upto to 20%)
Your Key Responsibilities:
- Lead Data Scientists and Data Engineers to drive product roadmap, innovation and build data-driven solutions to add lift to key performance metrics
- Investigate the feasibility of applying scientific principles and concepts to business problems
- Establish scalable, efficient, automated processes for large scale data analyses, solution development, model development, validation and implementation
- Work with engineering team and product managers to evangelize new algorithms and drive the implementation of large-scale complex ML models or algorithms in production
- Hire and develop top talent in machine learning and data science to accelerate the pace of data-driven decision making and innovation in the organization
- Clearly define project deliverables, timelines, measurement strategies and dependencies for the team and stakeholders. Examine, interpret and report results of analytical initiatives to stakeholders in leadership with a compelling and relevant story.
- Ideate and design POCs based on new ideas or technology, popularize new innovations in retail and analytics with internal/external stakeholders