Senior Specialist - Data Sciences @ LTM

Responsibilities Partners with lines of business to understand business problems and translate them into identifiable machine learning problems which can be delivered as technical solutions and actionable recommendations across the organization Coordinate with business teams to monitor outcomes and refine improve the machine learning models Work across the spectrum of statistical modelling including supervised unsupervised deep learning techniques to apply the right level of solution to the right problem Collaborate share best practices with data and software engineers to enable consistent deployment of highquality models that will scale across the companys ecosystem Own the code review process to ensure stringent coding guidelines are met by other data scientists data engineers Mentor lead Data Science engineers in choosing the right machine learning approach models utilizing open source languages such as R Python etc Lead data mining and collection procedures for all business use cases and guarantee data quality and integrity Utilize Data visualization tools to deliver insights to stakeholders and present technical solutions to nontechnical audience in a simple and clear manner Track emerging developments wrt technology tools practices etc in the open source data sciencemachine learningchatbot domain and leverage same for Client Build frameworks leveraging APIs to industrialize AI models across the organization Adhere to stringent quality assurance and documentation standards using version control and code repositories eg Git GitHub Markdown Requirements and Skills You should have bachelors or Masters degree in Computer Science Statistics or Mathematics Informatics Information Systems or another quantitative field You should have 7 years of experience in solving real life complex business problems using machine learning Handson experience in deploying these machine learning solutions to production is mandatory

In depth understanding of NLP LLM Generative AI RAG application development

Indepth understanding and modeling experience in supervised unsupervised reinforcement and deep learning models handson knowledge of data wrangling data cleaning preparation dimensionality reduction is required

Knowledge of vector algebra statistical and probabilistic modelling is highly desirable

Exploratory data analysis and hypothesis testing to identify ML opportunities is a plus

Experience in major machine learning frameworks such as Pytorch ScikitLearn Tensorflow Pandas SparkML etc

Fluency in programming skills such as Python R or other equivalent languages

Familiarity with databases like MySQL Oracle SQL Server NoSQL etc is desirable

Experience working with Amazon SageMaker or Azure ML Studio for deployments is required

Experience in data visualization software such as Tableau ELK etc is a plus