About the role
is looking for a Senior Data Scientist who can drive the AI/NLP engine that powers its service predictions. Our technology solves hitherto unsolved issues in the Service Intelligence space to create impactful category-defining products.
Responsibilities:
- Lead 's core AI/NLP technology that is at the heart of our service prediction engine.
- Understand our clients' data, identify signals from noise and build products that harness the intelligence in the signal.
- Interface with customer teams in our key industries to truly understand use cases and datasets and solve the prioritized product needs.
- Collaborate with the product, engineering, and leadership team in the company.
- Build a team of data scientists and data engineers that consists of the best minds in applied AI in the Service domain.
- Invent/Apply path-breaking NLP/AI techniques and tools. Stay on top of the latest research in academia and industry.
Requirements:
- Builder mindset: We are looking for individuals who are craving to create an impact in an AI-first Enterprise SaaS world.
- Ability to operate in a highly ambiguous and fast-paced environment. Passionate about creating and building new products.
- Experienced and talented NLP expert who has successfully rolled out Enterprise SaaS products in the CX space. Preferable Service. (7+ years).
- Experience across the enterprise NLP and data science spectrum - data engineering, data pipelines, processing large Enterprise datasets, deep learning modules to learn from the signal in the dataset etc. and finally make predictions. (7+ years).
- Critical to have diverse heterogeneous dataset experience - CRM data, Documents/Manuals, Device data such as log files, ERP/Engineering datasets, IoT etc.
- Expertise in data modelling and ontology detection techniques.
- A good combination of startup experience + large enterprise company mix is a huge plus.
- Experience in rolling out NLP products in production for verticals such as high-tech, Medical devices, Industrial appliances, and tech manufacturing is great to have.
Technical Skills:
- NLP toolkits such as NLTK, Spacy, Gensim, CoreNLP, and OpenNLP.
- Deep learning frameworks such as TensorFlow, PyTorch, Keras or Theono Python, and shell scripting.
- Algorithms for regression and classification such as Gradient Boosting, SVM, CART etc.
- Machine learning toolkits such as scikit-learn, NumPy, SciPy etc.
- Text analytics, data analytics, and deep learning architectures such as RNNs, LSTMs, CNNs, GRUs, Transformers etc.
- Computer vision and OCR techniques are an added advantage.