• Using statistical and machine learning techniques to analyse large-scale user data, including text data and chat logs; • Applying machine learning techniques for text mining and information extraction based on structured, semi-structured and unstructured data; • Contributing to services like chatbots, voice portals and dialogue systems • Input your own ideas to improve existing processes on services and products
- Strong grasp on Python and basic understanding of matrix algebra - Understanding of modern deep learning techniques like CNN, Attention, LSTM, etc - Experience with TensorFlow and Keras - Experience with Computer Vision and domain specific tools like opencv
JOB DESCRIPTION We're looking for Head, Machine learning (3+ years experience) for our company - Spotmentor Technologies. Right now our Technology team has 5 members and this is a head team member role and carries significant equity with it. We need someone who can lead the Machine learning function with both vision and hands-on work and is excited to use this area to develop B2B products for enterprise productivity. RESPONSIBILITIES • Collaborate with cross-functional team members to develop software libraries, tools, and methodologies as critical components of our computation platforms. • Also responsible for software profiling, performance tuning and analysis, and other general software engineering tasks. • Use independent judgment to take existing code, understand its function, and change/enhance as needed. • Work as a team leader rather than a member. REQUIREMENTS • Proficient in Python with sound knowledge in the machine learning libraries namely Scikit-learn, Numpy, Pandas, NLTK etc. • Experience with Deep Learning tools like TensorFlow, Keras, PyTorch etc and integrating using open source learning platforms is required. • Prior experience in building a fully functional Machine Learning Algorithm in the text analysis and multi-class classification with promising results. • Expert data scientist with professionalism in text classification, text analytics, regression and other machine learning algorithms. • Solid grasp of mathematical principles behind machine learning algorithms. • Proficient in using version control tools (Git, Mercurial etc). • Prior experience of using big data technologies like Hadoop, Spark etc. • Semantic Web experience is a big plus. • Should be from tier 1 colleges (IIT’s / NIT’s and BITS).
Artificial Intelligence Architect (Leader Level – 3-7yrs) Who is Mastercard? We are the global technology company behind the world’s fastest payments processing network. We are a vehicle for commerce, a connection to financial systems for the previously excluded, a technology innovation lab, and the home of Priceless®. We ensure every employee has the opportunity to be a part of something bigger and to change lives. We believe as our company grows, so should you. We believe in connecting everyone to endless, priceless possibilities. Overview Services and Data is helping to shape the future of data insights by leveraging billions of anonymized, aggregated transactions in a 10 petabyte date warehouse to help financial institutions, merchants, media, and governments manage their businesses more effectively. Advanced Analytics is charged with servicing clients by centralizing and optimizing the world class analytical, modeling, software coding, data sourcing, product development, product management, econometrics, and associated delivery capabilities of the MasterCard Advisors organization. It focuses on creating innovative technology solutions which leverage technology in the data science, artificial intelligence and analytics arenas; on enabling the field with industrialized, repeatable products; and on researching and incubating emerging technology to determine how they might apply to our customers and facilitate positive outcomes. • Are you motivated by developing new Analytical skills, leading to insights into issues and developing recommendations that add real value to clients? • Have you managed the client independently and effectively? • Do you want to play a key role in driving a world beyond cash? Role 1. Leading the formulation of artificial intelligence and machine learning solution objectives. Working on technical requirements based on user need. 2. Responsible for creating the framework of solutions that take data intensive and complex business challenges and provide easily consumed and automated outcomes 3. Using unique visualization techniques, condenses large volumes of complex ideas into elegant and simple visual models 4. Determine opportunities to exploit new data sources or leverage new outcomes from existing data sources, by applying new models and algorithms to create business value 5. Influences a client's strategic decisions by using deep industry expertise and deploying innovative Deep Learning analytics solutions in the operational systems Leadership Skills 1. Works closely with clients/internal stakeholders to understand their business needs and design a technical solution 2. Proving viability of the solution through mechanisms like proof-of-concepts 3. Thought Leadership in AI – Developing compelling audience-specific messages and tools. Capture and share best practices and insights internally and with partners and customers. 4. Self-driven, energetic, creative with ability to work in global teams. Excellent communication skills and a wide knowledge base, to convince the Stakeholders on application of AI/ML 5. Provide technical leadership to the team members in relevant topics on AI/ML 6. Adaptable - Takes in stride and constantly attunes to the changing needs of a highly dynamic business 7. Curious - our key contributors are always seeking to grow their knowledge, to gain new perspectives, and to find better ways forward by researching and showcasing latest AI tools, techniques and applications 8. Tenacious - self-starters who will take ownership of projects and bring them to completion despite difficulties or setbacks Functional and Technical Skills 1. Experience in building and implementing AI application in any of the 2 domains - Fraud, risk, marketing, finance, operations for Banks, Fintech, Ecommerce, merchants or retailers 2. Has a deep understanding of business value industry requirements and advanced analytic models (statistical, operations research, computing process) 3. Responsible for building applications using artificial intelligence/machine learning technology, applying latest industrial and academic developments, prefer Kaggle hackathon participant 4. Expertise in deep learning frameworks for Production Systems like Tensorflow, Keras (for RPD and neural net architecture evaluation), PyTorch and Xgboost, Caffe, Theono 5. Proficient in Deep Learning algorithm techniques like Random Forest, GBM, KNN, SVM, Bayesian, Text Mining techniques, Multilayer Perceptron, Neural Networks – Feedforward, CNN, LSTM’s GRU’s. Optimization techniques – Activity regularization (L1 and L2), Adam, Adagrad, Adadelta concepts; Cost Functions in Neural Nets – Contrastive Loss, Hinge Loss, Binary Cross entropy, Categorical Cross entropy; developed applications in KRR, NLP, Speech and Image processing 6. Expertise in classical Machine Learning algorithms like Logistic Regression, Decision trees, Clustering (K-means, Hierarchical and Self-organizing Maps), TSNE, PCA, Bayesian models, Time Series ARIMA/ARMA, Recommender Systems - Collaborative Filtering, FPMC, FISM, Fossil etc 7. Extensive experience in statistical tools and programming environments like Python, R, SAS, SQL 8. Experience with BIG DATA platforms - Hadoop, Hive, Spark, GPU Clusters for deep learning 9. Consulting and Project Management Experience preferred 10. Minimum Graduate degree in Mathematics/Computer Science/Engineering
We are looking for Freelance online Data Scientist Trainers who can work with us part - time with the following skills: Experience using statistical computer languages (R, Python etc.) to manipulate data and draw insights from large data sets. Should have strong programming & Good applied statistics skills, such as distributions, statistical testing, regression, etc. Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.Few examples are k-NN, Naive Bayes, SVM, Decision Forests,Random Forest ,Support vector machine,Principal component analysis. Experience using natural language processing techniques and Deep Learning using TensorFlow will be a plus. Should have minimum 5 years of relevant work experience.