The role of Data Science, Lead provides an opportunity to be a part of the Near Data Science team. You’ll join a team of experts in data science applied to location-based intelligence. The role requires you to apply your extensive knowledge to designing, developing, deploying and defining best practices for the Data Science team and to partner with key decision-makers in business, product, and engineering teams within the company.
As a Data Science-Lead, you will collaborate with your team members, Software Engineers, Data Engineers, and Data Analysts to develop data-driven products. You should have the ability to envision the Near Products and their feature enhancements; solve difficult challenges and set the pace. This is a hands-on role and you will be developing models and pipelines while also mentoring the rest of the team.
As part of the data science team at Near, one of the fastest-growing Enterprise SaaS companies, you will be part of a true start-up culture, where you are given the freedom to experiment and innovate new winning ways – a great opportunity for people who can work independently and are self-driven.
A Day in the Life
- Developing core data science models and capabilities that power the Near Platform and its SaaS products.
- Applying various data science methods such as time series forecasting, causal inference, machine learning methods, and reinforcement learning to understand the most important aspects of our product, users, and business.
- Advanced data analytics include processing structured (payments, telecom, page clicks, etc) and unstructured data in multiple formats (text, audio, video) spanning multiple domains including user profile data, geospatial data, network data, and retail data.
- Project management of data science projects to ensure they are delivered on time.
- Research and create intellectual property for the company that will benefit Near and its partners.
- Use nonparametric and probabilistic models to generate insights keeping in mind the bias-variance trade-off.
- Working closely with the Engineering team to operationalize and deploy the models.
- Partner with technology and business teams to build a superior data quality pipeline that will feed the models.
- Understand and prioritize the data science work based on cost-effectiveness and leveraging time management skills.
- Attend conferences and organize workshops/meet-ups to be in touch with the data science community.
What You Bring to the Role
- Hold an advanced degree in M.Tech/PhD in a quantitative field (e.g. Computer Science, Econometrics, STEM fields) plus.
- Overall 8-12 years of experience with at least a minimum of 5 years working experience at any data-driven company/platform, developing data science models and quantitative models.
- Ability to work independently with high energy, enthusiasm, and persistence.
- Must have exposure to handling multiple simultaneous projects and meeting deadlines and can work in a group setting as well as in an independent position.
- Must have thorough mathematical knowledge of correlation/causation, decision trees, classification, regression models, recommenders, probability, stochastic processes, distributions, priors, and posteriors.
- Understand the model lifecycle of cleansing/standardizing raw data, and feature creation/selection.
- Writing complex transformation logic to generate independent and dependent variables, model selection, tuning, A/B testing, and generating production-ready code.
- Knowledge of Numerical optimization, Linear/Non-linear/Integer programming, Statistics, and Combinatorial optimization is a plus.
- Familiarity with Python, Apache Spark (Java, Scala, Python), ANSI SQL, AWS Cloud, PyMC3/theano/tensorflow and other scientific python/R modules is a plus.
- Need to be comfortable writing code for model building and bootstrap, test, and own models through their lifecycle including DevOps and deploying into the cloud.
- The candidate is expected to have exceptional problem-solving, analytical, and organizational skills with a detail-oriented attitude.