Data Scientist Edge Talent Decisions

About Edge Talent Decisions

Who are we? At Edge, we believe that by simplifying employee data, large corporations will be able to resolve suboptimal talent management issues. After the pandemic, the necessity of managing a remote workforce has elevated the importance of this information. We have spent the last eight years gaining an understanding of the IT and BFSI workforces. This employee data was used to develop a sophisticated intelligence. EdGE graphTM is the brain behind our AI-based products. The graph was constructed using 11 million job descriptions and over 30 million profiles. Our products, such as Pathfinder, Recruit, and Mobility, are used by IT companies such as Wipro, HCL, UST Global, etc. to upskill, invest in, and retain their current workforce. It has enabled businesses to enhance their workforce availability, billing, and allocations, and to generate direct bottom-line impacts. The new order of talent decisions enables us to define, identify, and plan for a workforce that is prepared for the future. We provide organisations with end-to-end talent management solutions so that they have a 360-degree view of their talent supply chain. This allows them to make intelligent talent decisions and construct an intelligent workforce. Edge Networks was founded in 2012 in a Bangalore apartment with support from the National Skill Development Corporation of India (NSDC). We are a member of the NASSCOM Product Council and have been recognised as an innovative tech HR startup by Gartner, Deloitte, Equidam, NVIDIA, and Amazon. At Edge, we recognise that companies whose operations are centred on their employees and supported by data will have a productive organisation. This is how Edge uses technology for good.

Job Description

Experience: 3-5 Years
Location: Bangalore
Salary: 25-30 LPA
Notice Period: Immediate-30 days
Interview process: Round 1: Assignment and Round 2: Technical Interview

Responsibilities:
Design, Implement and Evaluate models and Design machine learning systems(NLP, text analytics, information retrieval, search, and recommendation systems, Knowledge graph, conversational system, Time-series based modelling, forecasting)
Design, development, evaluate and deploy innovative and highly scalable ML to improve the quality of products.
You should be passionate about working with data sets and be someone who loves to bring datasets together and use machine learning and analytical techniques to answer business questions and deliver actionable user-insights to build the best products and models.
Rapidly prototype integration of latest research in the field of ML/DL into the product.
Work closely with team of high performing data scientist and single ownership to identify opportunities, design, and assess improvements to ML Engine & Products

Role Skills:

• 3-5 years of hands-on experience in building machine learning systems for large datasets.
• Ability to break down and frame business problems into data science solutions and hands-on capability to create MVP out of it and run a DS project end to end independently.
• In-depth knowledge on supervised and unsupervised machine learning algorithms including classification, clustering, and regression.
• Experience in NLP (Sequence segmentation, Labeling and parsing, Knowledge extraction, Question answering, Multi text learning, ontology, taxonomy building), Machine Learning.
• Experience in Entity Extraction, Entity Linking, Clustering algorithms.
• Proficient in Math & Deep Learning (VAE, RNN, LSTM, CNN, attention models, Transfomer etc.), machine learning(svm, random forest), Clustering, topic modeling(LDA, LSA) and graph models.
• Experience in Python, Scikit-learn, Pytorch, Keras, Tensorflow
• Experience of implementing Deep Learning models into production
• Familiarity with distributed computing.
• Experience with SQL and/or No-SQL modelling.
• Excellent communication, analytical and problem-solving skills.
• B.S./B.S.E./MS degree in Applied Math, Data Science, Computer Science, Physics, or Similar Technical Field

Preferred Qualifications

• Passion to dive deep to resolve problems at their root.
• Experience in Data Governance, Data quality, Model Governance & MLops is a huge plus. Functional knowledge of platforms such as MLFLOW, Hopsworks/Sagemaker feature store/feast/Tecton, Seldon, DVC.
• Experience on building fair & explainable ML based product.
• Experience on federated learning, differential privacy, reinforcement learning.
• Experience on A/B testing, federated learning, differential privacy.
• Experience of git, flask, restful APIs.
• Experience working in a fast-paced, high tech environment.