About the role
You'll be our:Data Scientist
You'll be based at:Corporate office, Bangalore (IBC Knowledge Park)
You'll be aligned with:Business Intelligence Lead
You'll be a member of:Insights & Analytics Team
Our business journey captures a wealth of information at different touchpoints with the vehicle and customer during production, sales, marketing and vehicle ownership.
On the customer front, not only is there data captured through online touchpoints like the website, email marketing, digital marketing, app interactions, and social engagements, but we also accumulate data through physical touchpoints like the experience center, call interactions, vehicle service interactions or events.
We want someone who can be a part of the brand's journey; someone who can not only find questions that all this data can answer but also preempt those questions that market dynamics may present to us. A data explorer who owns the entire journey from deciding the structure of the experiments to culling out insights and recommending business actions.
What you'll do at Ather:
Advanced Statistical Analysis: As a data scientist, you will be involved in a lot of scenario planning / modeling, predictive or cognitive analytics through advanced machine learning and artificial intelligence tools & statistical techniques.
Data Querying: Querying & Structuring data in order to create data processing pipelines that automate the machine learning process and statistical tests.
Data analysis: Deep-dive various data sources for analysis, root causes, and uncover new patterns to answer key business questions for all functions within Ather including (but not limited to) business, production, finance, and HR through strong collaboration across the organization.
Storytelling: Present recommendations and insights of various analysis to key stakeholders in the most compelling manner to influence decision making.
Collaboration: Work with cross-functional teams, multiple systems, and vendor data to design, build, deploy the machine learning models, and utilize metrics to identify strong improvement opportunities. Collaborate with Data engineering and participate actively in discussions involving dashboards, data decisions, etc. for the organization.
Defining objectives & timelines: In cross-functional teams, make sure task completion timelines are estimated accurately and communicated. Prioritize tasks and share the necessary insights in the relevant swimlanes. Track program metrics and ensure that all programs are providing the business benefit as outlined in the original business case for the project.Represent the needs of the business, function, or region on an ongoing basis to drive process improvements.
Process adherence: Establish processes which are consistent with overall organization objectives and maintain process documentation.