Vahak - Data Scientist

Who Are We?

Vahak (https://www.vahak.in) is India's largest & most trusted online transport marketplace & directory for road transport businesses and individual commercial vehicle (Trucks, Trailers, Containers, Hyva, LCVs) owners for online truck and load booking, transport business branding and transport business network expansion. Lorry owners can find intercity and intracity loads from all over India and connect with other businesses to find trusted transporters and best deals in the Indian logistics services market. With the Vahak app, users can book loads and lorries from a live transport marketplace with over 5 Lakh + Transporters and Lorry owners in over 10,000+ locations for daily transport requirements.

Vahak has raised a capital of $5+ Million in a Pre-Series A round from RTP Global along with participation from Luxor Capital and Leo Capital. The other marquee angel investors include Kunal Shah, Founder and CEO, CRED; Jitendra Gupta, Founder and CEO, Jupiter; Vidit Aatrey and Sanjeev Barnwal, Co-founders, Meesho; Mohd Farid, Co-founder, Sharechat; Amrish Rau, CEO, Pine Labs; Harsimarbir Singh, Co-founder, Pristyn Care; Rohit and Kunal Bahl, Co-founders, Snapdeal; and Ravish Naresh, Co-founder and CEO, Khatabook.

Responsibilities for Data Scientist :

- Undertake preprocessing of structured and unstructured data

- Build predictive models and machine-learning algorithms

- Combine models through ensemble modeling

- Propose solutions and strategies to business challenges

- Collaborate with engineering and product development teams

- Present information using data visualization techniques

- Identify valuable data sources and automate collection processes

- Analyze large amounts of information to discover trends and patterns

- Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies.

Qualifications for Data Scientist :

- Proven experience as a Data Scientist and Advanced analytical knowledge of data

- Experience using business intelligence tools (e.g. Tableau, Power BI - not mandatory)

- Conceptual understanding of various modelling techniques, pros and cons of each technique

- Strong problem solving skills with an emphasis on product development.

- Programming advanced computing, Developing algorithms and predictive modeling experience

- Experience using statistical computer languages (R, Python, SLQ, etc.) to manipulate data and draw insights from large data sets.

- Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.

- Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.

- Demonstrated experience applying data science methods to real-world data problems