Details:

We're looking for a Sr. Data Scientist (NLP) who can take complete ownership of tasks in the Data Science team, hustle and get shit done while building and scaling our product at inFeedo. This person will be an individual contributor in a group of high-performing people that fuels our growth. In joining, you should love the idea of getting your hands dirty. You must love collaborating with others, seeing them flourish and grow, and continually challenging them to do their best work.

Our ask is a burning desire for scale, relentless passion for building cutting-edge products and undying love for technology.

No. of positions: 1

Min. Qualification:

• At least 2 years of work experience in NLP.
• Hands-on expertise with Python, SQL, and R.
• Experience in designing and building conversational agents. (Ex: Rasa NLU)
• Selecting features, building and optimizing classifiers using machine learning techniques.
• Text mining using state-of-the-art methods like clustering, classification, and information retrieval.
• Extending the company’s data with third party sources of information when needed.
• Enhancing data collection and data engineering procedures to include information that is relevant for building analytic systems.
• Good applied statistics skills, such as distributions, statistical testing, regression, etc.
• Processing, cleansing, and verifying the integrity of data used for analysis.
• Strong communication skills.

Those without these skill sets will not be accepted.

Brownie Points: Experience in scaling a small startup to a profitable mid-size SaaS business.

Our Current Tech Stack:

1. MEAN Stack (M=MySQL)
2. AWS is our IaaS
3. Our NLP has been built using R and Python

Skills Required:

NLP, R, Python, SQL

Roles:

1. Collaborate with different teams to create solutions for our most complex business work, from giving your input towards business models to building our A.I. architecture (and more).
2. Deliver actionable analytics that will move the product in the right direction.
3. Work with product management to design and launch data-science experiments and products.
   
4. Explore the information hidden in unstructured data, and assist take smarter decisions to deliver even better products and communicate insights clearly to various stakeholders
5. Support on-time, high-quality execution of both short and long-term projects and initiatives.
6. Grow and scale the organization, sustainably and responsibly. Define and track metrics to assess the quality and performance.