Senior Data Scientist

ABOUT THE COMPANY ElectrifAi Technologies Solution Pvt Ltd is America's oldest machine learning solutions company. With offices across the US, China and India, we hire people with a broad set of technical and -domain skills who can contribute to the creation of machine-learning solutions across verticals such as financial services, telecommunications, healthcare, consumer products etc. More details on our offerings can be seen on our website ), LinkedIn ) and at the following AWS SageMaker link: page=1 It was founded in 2004 and its Head Quarters is in New Jersey. They also have global offices in Noida and Shanghai. The CEO of the company is Edward Scott )
The company builds Machine Learning and Natural Language Processing Solutions in the below-mentioned areas: ● Customer Engagement ● Contact Centre Solutions ● Default and Cash Flow Prediction ● Demand Forecasting ● Inventory Optimization ● Supply Chain Network Optimization Some of the industries they serve include BFSI, Retail, Manufacturing, Hospitality, Transportation, Chemicals and Healthcare
ABOUT THE ROLE: As a Data Scientist at ElectrifAi Technologies Solution Pvt Ltd, you will be part of a global team of data scientists working on products and solutions for Fortune 500 companies. You will improve upon and build new ML use cases for our customers world-wide. You will collaborate with a multidisciplinary team of data scientists, software engineers, analysts and product management on a wide range of problems such as dynamic pricing, customer 360, demand forecasting, supply chain optimization, inventory management, spend analytics, NLP solutions, campaign management, churn management, cross-sell/upsell opportunities etc.
ROLES AND RESPONSIBILITIES ● Create state-of-the-art deep learning and ML algorithms and applications. ● Drive technical vision and strategy using ML to solve everyday business challenges. ● Help to define and improve large-scale Machine Learning solutions to develop personalization, recommendation, predictions, optimizations, and searches across industries. ● Define metrics, conduct A/B testing, and oversee statistical measurement of new algorithms and approaches. ● Thorough exposure to end-to-end ML operations and data science stack. ● Hands-on in Big Data technologies (such as Hadoop, Spark, and Storm) to build large-scale data mining pipelines. ● Work on state-of-the-art Natural Language Processing and Computer Vision algorithms to solve business problems. ● Work closely with engineering, product management, and delivery to build machine learning solutions incorporating data processing, feature engineering, and monitoring. ● Work with customers to understand their challenges and propose the best AI/ML solutions by clearly defined PoCs and prototypes followed by productizing.
REQUIREMENTS ● Master's degree in a quantitative discipline (e.g., Statistics, Operations Research, Bioinformatics, Economics, Computational Biology, Computer Science, Mathematics, Physics, Electrical Engineering, Industrial Engineering) or equivalent practical experience. ● Relevant hands on experience of Min 10 years. ● Expertise with statistical data analysis such as linear models, multivariate analysis, stochastic models, sampling methods. ● Proven experience in experimentation (a/b, causal inference, synthetic control etc), sophisticated data analysis, and or building machine learning models to solve real life business problems. ● Strong statistical and machine learning background. ● Hands on experience on various ML Algorithms such as Decision trees, Support vector machines (SVMs), Naive Bayes, KNN classification, K-Means, Random forest algorithm, Artificial neural networks (ANNs) and Recurrent neural networks (RNNs) ● Working experience on Deep Learning Models such as FNN, CNN, RNN, Transformers, Auto Encoders GANs, LSTM and RBM ● Experience with statistical software (e.g., R, Python, MATLAB, pandas) and proficiency with SQL and Hive / Spark (experience with streaming data a plus) ● Knowledge of natural language processing techniques and neural networks. ● Experience with Caffe/TensorFlow/Torch or similar deep learning framework

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