Lead Data Scientist

• Experience in Programing (Python, R, SQL, NoSQL,Spark) with ML tools & Cloud Technology (AWS, Azure, GCP)
• Experience in Python libraries such as numpy, pandas, scikit-learn, tensor-flow, scapy, scrapy, BERT etc.
• Good understanding in statistics, and ability to design statistical hypothesis testing to aid formal decision making.
• Develops predictive models using Machine Learning algorithms (SVM, Random Forest, Neural Network, Decision Tree, Logistic Regression, K-mean Clustering, linear regression, PCA etc.)
• Engaging with clients, understanding complex problem statements, and offering solutions in the domains of Retail, Pharma, Banking, Insurance, etc.
• Contribute to internal product development initiatives related to data science.
• Develop data science roadmap, and guide data scientist to meet their deliverables.
• Handling end-to-end client AI & analytics programs.

will be a combination of hands-on contribution, technical team management, and client interaction.

• Proven ability to discover solutions hidden in large datasets and to drive business results with their data-based insights
• Drive excellent project management required to deliver complex projects, including effort/time estimation.
• Be proactive, with full ownership of the engagement. Build scalable client engagement level processes for faster turnaround & higher accuracy
• Define Technology/ Strategy and Roadmap for client accounts, and guides implementation of that strategy within projects
• Run regular project reviews and audits to ensure that projects are being executed within the guardrails agreed by all stakeholders
• Manage the team-members, to ensure that the project plan is being adhered to over the course of the project
• Manage the client stakeholders, and their expectations, with a regular cadence of weekly meetings and status updates.
• Build a trusted advisor relationship with the IT management at clients and internal accounts leadership.
• Build business case for technological investments to be made for future needs and to remain competitive
• Ensure that billing and utilization of team members is maximized throughout the year

• Experience designing data science solutions to business problems
• Deep understanding of ML algorithms for common use cases in both structured and unstructured data ecosystems.
• Comfortable with large scale data processing and distributed computing
• Allocates workload among team members and by taking into consideration employee availability, skill set, and current workload when making assignments.
• Providing required inputs to sales, and pre-sales activities
• Excellent written and verbal communication skills

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