Specialist - Data Sciences
LTIMindtree · IT Services & Consulting
- Hyderabad, Kolkata
- On-site
- Posted today
- Data & AI
About the job
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