Senior Data Science Lead - Diverse Linx

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