We are looking for a Data Scientist who will support our IoT products, sales and marketing teams with insights gained from analyzing data.
The ideal candidate will be adept at using large data sets to find opportunities for product and process optimization and using models to test the effectiveness of different courses of action. They must have strong experience using a variety of data analysis methods, using a variety of data tools, building and implementing models, using/creating algorithms and creating/running simulations. They must have a proven ability to build products for mobile app. They must be comfortable working with a wide range of functional teams. The right candidate will have a passion for discovering solutions hidden in large data sets and working with team to improve product outcomes.
1. Collaborate with cross-functional teams including but not limited to Engineering, Products, Operations, Sales, Marketing, etc. to breakdown complex problems and recommend data science products.
2. Assess the effectiveness and accuracy of new data sources and data gathering techniques.
3. Develop custom data models and algorithms to apply to data sets.
4. Use machine learning and analytical techniques to create scalable solutions for problems.
5. Contribute to the development/ deployment of machine learning algorithms.
6. Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation.
7. Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes
1. Degree (B.Tech, MS, PhD or equivalent) in Computer Science, Mathematics, Operational Research, Statistics or Natural Sciences
2. 1-7 years of work experience in data science and statistical modeling
3. Strong problem solving skills with an emphasis on product development.
4. Experience working with and creating data architectures.
5. A very clear understanding of probability and statistics, analytical approach to problem solving, and capability to think critically on a diverse array of problems
6. Supervised Machine Learning Algorithms: Predictive Analytics, Logistic Regression, Bayesian Approach, Decision Trees, Support Vector Machines. Neural Networks etc.
7. Understanding of advanced algorithms (i.e. Deep Learning, Probabilistic Graph Models) will be good to have
8. Familiarity with statistical methods such as hypothesis testing, forecasting, time series analysis, etc - gained through work experience or graduate level education
9. Expertise in following languages: Python, Java, C++, R, SQL etc.
10. Experience with relational databases NoSQL databases such as MongoDB, Elastic Search, Redis or any graph database
11. Skilled at data visualization and presentation
Most importantly, an inquisitive mind, an ability for self-learning and abstraction along with a risk appetite for experimentation and failure
We are a home-tech start-up, powered by a mix of Image Processing, VR, IOT and Data Analytics. We are solving energy issues of India by using un-utilised rooftops for solar, and by providing sense and control of every appliance in one's house.