About Paytm Labs:
At Paytm Labs, we build technologies that empowers Paytm India, the world’s fastest-growing mobile payments and commerce ecosystem. In addition to the Paytm Canada app. We use our skills and our biggest asset – data, to make our dent in this universe.
We are committed to offering the most transparent, secure, and personalized consumer experience to over 230 million users. We believe that this kind of scale and the unique problems that it presents attracts curious candidates like yourself.
Job Description:
As an Applied Statistician – Data Science, you are required to develop statistical data products in the domains of advertising technology and marketing automation primarily based on the python language using Jupyter Notebook and its related tools, and work with data stored in databases, S3 or CSV files. You will liaise with machine learning engineers, data scientists and business users to develop data products, which can be readily accessed and used both internally and externally.
You will collaborate with Machine Learning engineers to evaluate models and communicate the model performance in notebooks. You are passionated to write clean code and automate analysis. You possess exceptional communication skill to understand the requirements from both the engineers and the business users. You are skilled in the processing and cleaning data, creating statistical inference or predictive models, running experiments, plotting those results, creating reports and providing insights to stakeholders.
You will be working in the machine learning team and if you want to contribute to the mission critical applications using data-driven approach, this is the place for you.
Responsibilities
- Develop data products, primarily based on the python language and associated tools
- Suggest statistical approaches and conduct statistical analysis
- Work closely with Machine Learning engineers for machine learning model development (that includes interpreting machine learning model predictions and select metrics for model offline and online evaluation)
- Collaborate with business users to develop new data products
- Interpreting data within the context of the project
- Prepare reports from statistical analyses for review including graphs, tables, and interpretation
Qualifications
- Minimum of a degree or equivalent in data analysis or numerical discipline (preferably a post-graduate degree in statistics), in addition to 1-3 years of relevant experience in industry focused on payment, advertising or marketing
- Preparing analysis datasets and explore data prior to statistical analyses
- Proficiency in python programming
- Experience analyzing large amounts of data
- Strong SQL programming skills
- Experience with varied statistical methods and Bayesian methods
- Strong interpersonal skills
- Have basic knowledge in machine learning
- Ability to work in a diverse team environment
- Strong verbal and written communication skills
- Ability to work independently with some supervision
- Excellent attention to detail and proven ability to learn new skills
What we Offer!
- We are proud to announce that we have been certified as a Great Place to Work!
- A collaborative, open work environment that fosters ownership, creativity, and urgency
- Enrolment in the Group Health Benefits plan right from Day 1, no waiting period
- Fuel for the day: Weekly delivery of groceries and all types of snacks to our office
- All types of signature drinks from coffee to lattes to cappuccinos
- Catered lunch and desserts on a monthly basis!
- Ping Pong and Pool: Become the next Paytm Labs Table Tennis/ Pool champ!
- And so much more!
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We thank all applicants, however, only those selected for an interview will be contacted.
Paytm Labs is committed to meeting the accessibility needs of all individuals in accordance with the Accessibility for Ontarians with Disabilities Act (AODA) and the Ontario Human Rights Code (OHRC). Should you require accommodations during the recruitment and selection process, please let us know. Paytm Labs is an equal opportunity employer.