Data Engineer

• Your responsibilities:
• Build, improve and extend NLP capabilities
• Research and evaluate different approaches to NLP problems
• Must be able to write code that is well designed, produce deliverable results
• Write code that scales and can be deployed to production

• Fundamentals of statistical methods is a must
• Experience in named entity recognition, POS Tagging, Lemmatization, vector representations of textual data and neural networks - RNN, LSTM
• A solid foundation in Python, data structures, algorithms, and general software development skills.
• Ability to apply machine learning to problems that deal with language
• Engineering ability to build robustly scalable pipelines
• Ability to work in a multi-disciplinary team with a strong product focus

Responsibilities

• Work on execution and scheduling of all tasks related to assigned projects' deliverable dates
• Optimize and debug existing codes to make them scalable and improve performance
• Design, development, and delivery of tested code and machine learning models into production environments
• Work effectively in teams, managing and leading teams
• Provide effective, constructive feedback to the delivery leader
• Manage client expectations and work with an agile mindset with machine learning and AI technology
• Design and prototype data-driven solutions

Eligibility

• Highly experienced in designing, building, and shipping scalable and production-quality machine learning algorithms in the field of Python applications
• Working knowledge and experience in NLP core components (NER, Entity Disambiguation, etc.)
• In-depth expertise in Data Munging and Storage (Experienced in SQL, NoSQL, MongoDB, Graph Databases)
• Expertise in writing scalable APIs for machine learning models
• Experience with maintaining code logs, task schedulers, and security
• Working knowledge of machine learning techniques, feed-forward, recurrent and convolutional neural networks, entropy models, supervised and unsupervised learning
• Experience with at least one of the following: Keras, Tensorflow, Caffe, or PyTorch

What you will do:

• Understand the process of CaaStle business teams, KPIs, and pain points
• Build scalable data products, self-service tools, data cubes to analyze and present data associated with acquisition, retention, product performance, operations, client services, etc.
• Closely partner with data engineering, product, and business teams and participate in requirements capture, research design, data collection, dashboard generation, and translation of results into actionable insights that can add value for business stakeholders
• Leverage advanced analytics to drive key success metrics for business and revenue generation
• Operationalize, implement, and automate changes to drive data-driven decisions
• Attend and play an active role in answering questions from the executive and/or business teams through data mining and analysis

We would love for you to have:

• Education: Advanced degree in Computer Science, Statistics, Mathematics, Engineering, Economics, Business Analytics or related field is required
• Experience: 2-4 years of professional experience
• Proficiency in data visualization/reporting tools (i.e. Tableau, Qlikview, etc.)
• Experience in A/B testing and measure performance of experiments
• Strong proficiency with SQL-based languages. Experience with large scale data analytics technologies (i.e., Hadoop and Spark)
• Strong analytical skills and business mindset with the ability to translate complex concepts and analysis into clear and concise takeaways to drive insights and strategies
• Excellent communication, social, and presentation skills with meticulous attention to detail
• Programming experience in Python, R, or other languages
• Knowledge of Data mining, statistical modeling approaches, and techniques

CaaStle is committed to equality of opportunity in employment. It has been and will continue to be the policy of CaaStle to provide full and equal employment opportunities to all employees and candidates for employment without regard to race, color, religion, national or ethnic origin, veteran status, age, sexual orientation, gender identity, or physical or mental disability. This policy applies to all terms, conditions and privileges of employment, such as those pertaining to training, transfer, promotion, compensation and recreational programs.

Job Responsibilities:-

• Develop robust, scalable and maintainable machine learning models to answer business problems against large data sets.
• Build methods for document clustering, topic modeling, text classification, named entity recognition, sentiment analysis, and POS tagging.
• Perform elements of data cleaning, feature selection and feature engineering and organize experiments in conjunction with best practices.
• Benchmark, apply, and test algorithms against success metrics. Interpret the results in terms of relating those metrics to the business process.
• Work with development teams to ensure models can be implemented as part of a delivered solution replicable across many clients.
• Knowledge of Machine Learning, NLP, Document Classification, Topic Modeling and Information Extraction with a proven track record of applying them to real problems.
• Experience working with big data systems and big data concepts.
• Ability to provide clear and concise communication both with other technical teams and non-technical domain specialists.
• Strong team player; ability to provide both a strong individual contribution but also work as a team and contribute to wider goals is a must in this dynamic environment.
• Experience with noisy and/or unstructured textual data.

knowledge graph and NLP including summarization, topic modelling etc

• Strong coding ability with statistical analysis tools in Python or R, and general software development skills (source code management, debugging, testing, deployment, etc.)
• Working knowledge of various text mining algorithms and their use-cases such as keyword extraction, PLSA, LDA, HMM, CRF, deep learning & recurrent ANN, word2vec/doc2vec, Bayesian modeling.
• Strong understanding of text pre-processing and normalization techniques, such as tokenization,
• POS tagging and parsing and how they work at a low level.
• Excellent problem solving skills.
• Strong verbal and written communication skills
• Masters or higher in data mining or machine learning; or equivalent practical analytics / modelling experience
• Practical experience in using NLP related techniques and algorithms
• Experience in open source coding and communities desirable.

Able to containerize Models and associated modules and work in a Microservices environment

• Gathering project requirements from customers and supporting their requests.
• Creating project estimates and scoping the solution based on clients’ requirements.
• Delivery on key project milestones in line with project Plan/ Budget.
• Establishing individual project plans and working with the team in prioritizing production schedules.
• Communication of milestones with the team and to clients via scheduled work-in-progress meetings
• Designing and documenting product requirements.
• Possess good analytical skills - detail-orientemd
• Be familiar with Microsoft applications and working knowledge of MS Excel
• Knowledge of MIS Reports & Dashboards
• Maintaining strong customer relationships with a positive, can-do attitude