Data Science Manager

As Manager-Delivery, you will be responsible for a wide range of engagements listed below: 

Responsibilities 

As Manager-Delivery, you will be responsible for a wide range of engagements listed below: 

• Collaborate with the Engagement Manager, Account Delivery Manager, and client stakeholders to gather business requirements for the project. 
• Develop a comprehensive project plan that aligns with the scope and objectives of the project. 
• Develop appropriate solution design that will help client achieve their goals.
• Assign delivery team members to different activities suited to their individual skills. 
• Lead the execution of project activities according to the project plan. Monitor the project, track milestones, and adhere to agreed-upon timelines and scope. 
• Accountable for the delivery quality of the project in question. 
• Comply with all the critical dimensions of the delivery scorecard, report as-is facts on those dimensions, and develop and execute action plans to improve delivery scores. 
• Lead internal scrum meetings and stand-ups with the clients and Weekly Business Reviews with the clients. 
• Ensure compliance with best practices and established processes for quality assurance—for example, using quality assurance checklists, coding best practices, peer reviews, and documentation. 
• Provide both business and technical guidance to the delivery team. 
• Coach individuals in the team and build a high-performance workplace. 
• Establish an environment of mutual trust and respect and encourage the team to experiment with new delivery ideas. 
• Review the team's deliverables before sharing them with clients, including codes, presentations, worksheets, emails, etc. 

Required Skills (Must have)  
Tech 

• Advanced knowledge of probability and statistics 
• Advanced knowledge of Practical Machine Learning and awareness of the key pitfalls in machine learning and approaches to addressing them 
• Intermediate knowledge levels in SQL and Python 
• Intermediate knowledge of project management methodologies and tools 
• Intermediate knowledge of MS Office applications: MS Excel, MS PowerPoint, and MS Word 

 
Non-tech 

• Strong business acumen with an ability to assess the financial impact of decisions, both in running the delivery team and delivering solutions to clients. 
• Ability to storyboard presentations effectively and hold conversations with mid-management-level clients. 
• Ability to recognize pragmatic alternatives vis-à-vis a perfect solution and get the delivery teams on board to pursue them, balancing time priorities with potential business impact. 
• Strong people skills, including conflict resolution, empathy, communication, listening, and negotiation. 
• Provide leadership and mentorship to the delivery team. 
• Self-driven with a strong sense of ownership. 

  
Required Skills (Good to have) 
Tech 

• Advanced knowledge of project management methodologies and tools 
• Advanced knowledge levels in SQL and Python 
• Intermediate to advanced knowledge in other areas of data science—namely, technical areas such as time series forecasting, Bayesian data analysis, Operations Research, and analytics domain areas such as Pricing analytics, Media Mix Modeling, B2B/B2C Customer analytics, etc. 

  
Non-tech 

• Solution proposals, collaborating with growth, customer success, and central solutioning functions 

 
Educational Qualifications 

• An undergraduate degree in engineering, statistics, mathematics, computer science, or another technical field. 
• For those with an undergraduate degree in non-technical fields, relevant prior work experience and technical aptitude will be important. 

  
Years of experience 

• 7-10 years of relevant work experience.