Assistant Manager- Founder's Office

Responsibilities

Work directly with the Senior Management to solve key organisational problems and develop new processes to scale the company

Research, model, evaluate, and plan organisational scale up

Work on financial planning and forecasting

Independently own and execute projects of high importance for the company

Identify, implement and onboard key systems to smoothen processes

Define, track and report KPIs for multiple functions to understand the momentum and proactively flag issues

Be a first principal thinker to understand a problem and propose a solution

Creating effective presentations for internal and external business stakeholders

Qualifications

MBA from a top tier management college

Minimum 3 - 5 years of experience working as a management / strategy consultant or in a fast-paced startup environment. 4-6 years of overall experience

A keen interest in learning about business

You are an entrepreneur at heart, i.e. you are not only excited about startups but also really understand what it is like to work in one

You do not wait for instructions and guidelines but believe in taking end-to-end ownership of things

You are excited to learn new things and do not shy away from going above and beyond the traditional growth paths. You have strong communication skills

You can quickly adapt to the changing environment and are quick to pick up new skills if required to get the job done

Preferred Skills

Past experience starting your own company or as an early employee of a high growth startup

Understanding of the data ecosystem and consulting / services business model

About Sigmoid

Sigmoid enables business transformation using data and analytics, leveraging real-time decisions through insights by building modern data architectures using cloud and open source technologies. Some of the world’s largest data producers engage with Sigmoid (Fortune1000) to solve complex business problems. Sigmoid brings deep expertise in data engineering, predictive analytics, AI / ML, and Data Ops.