Lead Software Engineer - Data Science

Responsibilities
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 high-quality models that will scale across the company’s ecosystem
Own and insure stringent coding guidelines with 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 non-technical audience in a simple and clear manner
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 (e.g., Git, GitHub, Markdown)
Requirements and Skills
You should have bachelor’s or Master’s degree in Computer Science, Statistics or Mathematics, Informatics, Information Systems or another quantitative field
You should have 6+ years of experience in solving real life complex business problems using machine learning. Hands-on experience in deploying these machine learning solutions to production is mandatory.
3+ experience in Deep Learning, NLP and/or Computer Vision is must. LLM knowledge and architecture is plus.
Cloud Handson either in AWS or Azure is must.
In-depth understanding and modeling experience in supervised, unsupervised, reinforcement and deep learning models; hands-on 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, Scikit-Learn, 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
Strong analytical and critical thinking skills. You should also have a business mindset, swift to identify risk situations and opportunities, and able to generate creative solutions to business problems
Effective communication skills (written and verbal) to properly articulate complicated statistical models/ reports to management and other IT development partners

Requirements