Data Scientist - Operations Research
Helpshift-Data Science is looking for experienced folks having prior background in building Operations Research/Capacity Planning products from scratch. You should have worked in a research environment before and should be ready to take a deep dive into data and algorithms. You get to be part of a small team of seasoned data scientists who are working on some of the most complex problems in customer services domain such as intent classification, topic modelling, sentiment analysis, smart replies, etc.
Helpshift is at the forefront of innovation in the customer service space and you'll get to solve business critical problems using AI and ML. You will be working in a fast-paced start-up where everyone is data savvy. Surrounded by talented people from different backgrounds and working with unique data; you will be challenged constantly. At Helpshift, you get to work in a collaborative environment at one of fastest growing companies in its domain.
About the Role:
We are looking for people having subject matter expertise in at least one of the following areas:
1. Mathematical optimisation
2. Capacity Planning and Time Series Analysis
Our process gives you full ownership over the projects. Ideally, you will be expected to collaborate with the product management team for defining your own problem and drafting a project plan for solving it - from conceptualisation, research, development to production. This job helps you to challenge your analytical knowhow beyond classification, clustering, ranking and regression.
- You will drive data culture and evangelize use of data science in all possible aspects of business.
- Research and development of bleeding edge OR models and algorithms.
- Discovering new applications of classical OR algorithms like IP, MIP, LP and MLP.
- Iterative improvement of the currently deployed models.
- You get a chance to build OR framework at scale for different aspects of business
- Enhancing existing operations related modules including assignment of tickets to support agents, workflow automation, etc.
- Excellent problem solving skills, with an ability to communicate even complex ideas in clear manner
- Strong work ethics like sense of collaboration and ownership, result orientation, being a team player
- Proficiency in R, Python, Mathematica, MATLAB or related tools used from data handling to modeling to deployment
- Knowledge of statistical concepts related to data driven design like multivariate testing, DOEs
- Good understanding of applying OR techniques to complex business problems
- MS in Computer Science, Engineering, Statistics, Operations Research or related field with research experience in OR
- Minimum three years of post Masters experience in one of the following domains: (1) Implementation of linear, non-linear and/or mixed integer programming models for capacity planning (2) Pattern recognition and forecasting using Time Series analyses
- Familiarity with concepts in probability and statistics, including experimental design, predictive modeling, optimization, and causal inference
- Familiarity with concepts in linear algebra, including matrix manipulation, Gaussian Elimination and Eigenvalue problems
- Deep knowledge in the theory of convex optimization, first-order iterative optimization algorithms (gradient descent, conjugate gradients etc.), and mathematical programming (IP, MIP, LP, MLP, etc.)
- A strong sense of connecting technical work to product impacts
- Expert knowledge of a statistical computing language such as R, Python, Mathematica or MATLAB.
- Excellent written and verbal technical communication skills
- Familiarity with a scripting language and/or shell scripting
- Preferred: Ph.D./Post-Doc in Computer Science, Engineering, Statistics, Operations Research or other relevant technical field
- Preferred: Experience with large-scale distributed systems
- Preferred: Experience with tools in the Hadoop ecosystem such as Hive, Pig, or Spark
- Preferred: Knowledge of functional programming languages like Lisp, Haskell, Clojure
- Past experience in Machine Learning
- Past experience in Customer Services/Contact Centers domain
Helpshift bridges the disconnect between conventional customer service channels—like email and phone support—and a growing consumer base that does more on mobile phones and has a strong preference for messaging as the primary mode of communication. Through Helpshift's AI-powered support platform, companies can resolve issues more efficiently, boosting customer satisfaction in the process. Companies such as Xfinity Home, Microsoft, Virgin Media, Zynga, Viacom, and hundreds of other leading brands use the Helpshift platform to provide messaging-first customer support. Helpshift is installed on two billion devices worldwide and serves more than 820 million active consumers monthly. Founded in 2011 and headquartered in San Francisco, Helpshift has raised more than $38 million from True Ventures, Nexus Venture Partners, Visionnaire Ventures, Intel Capital, Cisco Investments, Salesforce Ventures, and Microsoft Ventures. To learn more about Helpshift, visit helpshift.com and follow @helpshift on Twitter.
Helpshift embraces diversity. We are proud to be an equal opportunity workplace and do not discriminate on the basis of sex, race, color, age, sexual orientation, gender identity, religion, national origin, citizenship, marital status, veteran status, or disability status.