We are hiring Lead Data Scientists (8-12 yrs) with strong programming skills in Python and exposure in Data Science-Machine Learning and Pricing.

Job Description:

Graduate degree in a quantitative field (CS, statistics, applied mathematics, machine

learning, or related discipline)

Good programming skills in Python with strong working knowledge of Pythons numerical,

data analysis, or AI frameworks such as NumPy, Pandas, Scikit-learn, etc.

Experience with SQL, Excel, Tableau/ Power BI, PowerPoint

Predictive modelling experience in Python (Time Series/ Multivariable/ Causal)

Experience applying various machine learning techniques and understanding the key

parameters that affect their performance

Experience of building systems that capture and utilize large data sets to quantify

performance via metrics or KPIs

Excellent verbal and written communication

Comfortable working in a dynamic, fast-paced, innovative environment with several ongoing

concurrent projects.

Roles & Responsibilities:

Lead a team of Data Engineers, Analysts and Data scientists to carry out following activities:

Connect with internal / external POC to understand the business requirements

Coordinate with right POC to gather all relevant data artifacts, anecdotes, and hypothesis

Create project plan and sprints for milestones / deliverables

Spin VM, create and optimize clusters for Data Science workflows

Create data pipelines to ingest data effectively

Assure the quality of data with proactive checks and resolve the gaps

Carry out EDA, Feature Engineering & Define performance metrics prior to run relevant

ML/DL algorithms

Research whether similar solutions have been already developed before building ML models

Create optimized data models to query relevant data efficiently

Run relevant ML / DL algorithms for business goal seek

Optimize and validate these ML / DL models to scale

Create light applications, simulators, and scenario builders to help business consume the

end outputs

Create test cases and test the codes pre-production for possible bugs and resolve these bugs

proactively

Integrate and operationalize the models in client ecosystem

Document project artifacts and log failures and exceptions.

Measure, articulate impact of DS projects on business metrics and finetune the workflow

based on feedbacks.

Lead Data Scientist