Senior Data Science Lead - Diverse Lynx

" Ability to understand a problem statement and implement analytical solutions techniques independently or with minimal supervision

" Work and collaborate with other teams to deliver and create value

" Identify valuable data sources and automate collection processes

" Undertake preprocessing of structured and unstructured data

" Analyze large amounts of information to Client trends and patterns

" Build predictive models and machine-learning algorithms

" Combine models through ensemble modeling

" Present information using data visualization techniques

" Propose solutions and strategies to business challenges

" should have good hands on experience on basic non linear Client techniques and able to explain the previous project experience PL language : Python Qualifications:

" 7-12 years of relevant experience in data science, advanced statistics or business analytics

" Ability to Client effective solutions to complex problems. Strong skills in data-structures and algorithms.

" Experience of working on a project end-to-end: problem scoping, data gathering, EDA, modeling, insights, and visualizations

" Model building using various statistical tools (Python, etc.) and data modeling techniques using SQL, etc. along with regular validation of models as advised by management.

" Grasp at databases including RDBMS, NoSQL, MongoDB etc.

" Experience in data mining

" Exceptional interpersonal skills and written communication skills

" Strong experience in documenting model methodologies, performance and hypothesis testing

" Ability to evaluate risks and provide recommendations / solutions in a timely manner

" Experience using statistical computer languages (Python) to manipulate data and draw insights from large data sets. Experience working with data architectures.

" Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.

" Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications

" Must have MLOps experience