Specialist - Data Sciences

Job Summary Lead and innovate advanced data science projects by leveraging strong research skills and deep expertise in machine learning and optimization models Job Description Understand and analyze project requirements with a researchoriented mindset Review existing machine learning and optimization models to identify improvement opportunities Lead analytics projects providing strategic guidance and mentorship to the team Conduct handson development of analytics and data science models Perform exploratory data analysis EDA to uncover insights and patterns Engineer features to enhance model performance Build robust statistical and machine learning models including deep neural networks DNN Validate and pilot machine learning models with rigorous testing Continuously tune and improve models based on performance metrics Apply strong theoretical knowledge of ML algorithms and statistics in practical scenarios Utilize expertise in Python and Spark Scala or PySpark for scalable data processing Demonstrate strong stakeholder management and communication skills Exhibit a proactive research attitude to stay updated with the latest advancements in data science Preferably hold a PhD or equivalent research experience in a relevant field Experience in cloud environments such as GCP or Azure is a plus Domain experience in Consumer Packaged Goods CPG is advantageous Roles and Responsibilities Lead and manage multiple data science projects from conception to deployment Drive innovation by applying research methodologies to solve complex business problems Mentor and guide team members to foster a culture of continuous learning and improvement Collaborate with crossfunctional teams and stakeholders to align data science solutions with business goals Design and implement scalable machine learning pipelines 
 Conduct thorough model validation and ensure robustness and reliability 
 Stay abreast of emerging trends and technologies in data science and machine learning 
 Contribute to knowledge sharing through documentation presentations and publications when applicable