Position : Data Scientist
- Collaborate with cross-functional teams including but not limited to Engineering, Products, Operations, Sales, Marketing, Security, Customer Service, etc. to breakdown complex business problems and recommend data science products.
- Use advanced statistics and machine learning on large scale multidimensional data and generate actionable insights that will be leveraged to drive operations and develop strategies for Delhivery.
- Use machine learning and analytical techniques to create scalable solutions for business problems.
- Contribute to the development/ deployment of machine learning algorithms.
- Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation.
- Disseminate original research in peer reviewed journals and conferences.
- Degree (B.Tech, MS, PhD or equivalent) in Computer Science, Mathematics, Operational Research, Statistics or Natural Sciences
- 1-7 years of work experience in data science and statistical modeling for DS, 3+ for Sr. DS
- A very clear understanding of probability and statistics, analytical approach to problem solving, and capability to think critically on a diverse array of problems
- Supervised Machine Learning Algorithms: Logistic Regression, Bayesian Approach, Decision Trees, Support Vector Machines. Neural Networks, Ensemble Methods, Feature selection techniques etc
- Understanding of advanced algorithms (i.e. Deep Learning, Probabilistic Graph Models) will be good to have
- Familiarity with statistical methods such as hypothesis testing, forecasting, time series analysis, etc – gained through work experience or graduate level education
- Expertise in at least one of the following languages: Python, Java, C++
- Experience with relational databases NoSQL databases such as MongoDB, Elastic Search, Redis or any graph database
- Experience in handling geospatial data such as PostGIS will be appreciated
- Skilled at data visualization and presentation
- Good communication skills with both technical and business people
- Experience with big data tools like Spark, Hadoop is a plus
- Publications in peer-reviewed journals will count in your favour
- Most importantly, an inquisitive mind, an ability for self learning and abstraction along with a risk appetite for experimentation and failure
Engineering Information Technology
Logistics and Supply Chain