About Saama Technologies
● Lead the development of AI/ML related applications as it matures into lean, high performing agile teams.
● Own the vision and execution of developing and integrating AI & machine learning into all aspects of the platform.
● Drive innovation through the use of technology and unique ways of applying it to business problems
● A well-developed portfolio of past software development, composed of some mixture of professional work, personal projects and open source contributions will be considered a huge plus.
The candidate must have 2-3 years of experience in the following domain:
● Deep understanding & experience of working on Machine Learning and AI powered applications
● Build and train AI chatbot models
● Experience with writing production and scalable code
● Must have proficiency in Python programming
● Experience with NLP, NLU, Text Analytics, Rasa, MongoDB, OpenCV, CNN, LSTM, and BERTs will be a plus.
● Familiarity with DL frameworks (e.g. PyTorch, TensorFlow, etc.)
● Deploy source code by way of encryption and setting up Docker on cloud servers.
● Proficiency in RESTful APIs
● Have a basic understanding of setting up, deploying & managing cloud servers like AWS, GCP, etc.
● Experience working with GIT
● Fantastic Work Culture
● Competitive Salary & Benefits
● Work from Office (Location- Noida)
- Passionate about search & AI technologies. Open to collaborating with colleagues & external contributors.
- Good understanding of the mainstream deep learning models from multiple domains: computer vision, NLP, reinforcement learning, model optimization, etc.
- Hands-on experience on deep learning frameworks, e.g. Tensorflow, Pytorch, MXNet, BERT. Able to implement the latest DL model using existing API, open-source libraries in a short time.
- Hands-on experience with the Cloud-Native techniques. Good understanding of web services and modern software technologies.
- Maintained/contributed machine learning projects, familiar with the agile software development process, CICD workflow, ticket management, code-review, version control, etc.
- Skilled in the following programming languages: Python 3.
- Good English skills especially for writing and reading documentation
Expertise in handling large amount of data through Python or PySpark
Conduct data assessment, perform data quality checks and transform data using SQL
and ETL tools
Experience of deploying ETL / data pipelines and workflows in cloud technologies and
architecture such as Azure and Amazon Web Services will be valued
Comfort with data modelling principles (e.g. database structure, entity relationships, UID
etc.) and software development principles (e.g. modularization, testing, refactoring, etc.)
A thoughtful and comfortable communicator (verbal and written) with the ability to
facilitate discussions and conduct training
Track record of strong problem-solving, requirement gathering, and leading by example
Ability to thrive in a flexible and collaborative environment
Track record of completing projects successfully on time, within budget and as per scope
- Expert software implementation and automated testing
- Promoting development standards, code reviews, mentoring, knowledge sharing
- Improving our Agile methodology maturity
- Product and feature design, scrum story writing
- Build, release, and deployment automation
- Product support & troubleshooting
Who we have in mind:
- Demonstrated experience as a Java
- Should have a deep understanding of Enterprise/Distributed Architecture patterns and should be able to demonstrate the relevant usage of the same
- Turn high-level project requirements into application-level architecture and collaborate with the team members to implement the solution
- Strong experience and knowledge in Spring boot framework and microservice architecture
- Experience in working with Apache Spark
- Solid demonstrated object-oriented software development experience with Java, SQL, Maven, relational/NoSQL databases and testing frameworks
- Strong working experience with developing RESTful services
- Should have experience working on Application frameworks such as Spring, Spring Boot, AOP
- Exposure to tools – Jira, Bamboo, Git, Confluence would be an added advantage
- Excellent grasp of the current technology landscape, trends and emerging technologies
As a Senior Engineer - Big Data Analytics, you will help the architectural design and development for Healthcare Platforms, Products, Services, and Tools to deliver the vision of the Company. You will significantly contribute to engineering, technology, and platform architecture. This will be done through innovation and collaboration with engineering teams and related business functions. This is a critical, highly visible role within the company that has the potential to drive significant business impact.
The scope of this role will include strong technical contribution in the development and delivery of Big Data Analytics Cloud Platform, Products and Services in collaboration with execution and strategic partners.
- Design & develop, operate, and drive scalable, resilient, and cloud native Big Data Analytics platform to address the business requirements
- Help drive technology transformation to achieve business transformation, through the creation of the Healthcare Analytics Data Cloud that will help Change establish a leadership position in healthcare data & analytics in the industry
- Help in successful implementation of Analytics as a Service
- Ensure Platforms and Services meet SLA requirements
- Be a significant contributor and partner in the development and execution of the Enterprise Technology Strategy
- At least 2 years of experience software development for big data analytics, and cloud. At least 5 years of experience in software development
- Experience working with High Performance Distributed Computing Systems in public and private cloud environments
- Understands big data open-source eco-systems and its players. Contribution to open source is a strong plus
- Experience with Spark, Spark Streaming, Hadoop, AWS/Azure, NoSQL Databases, In-Memory caches, distributed computing, Kafka, OLAP stores, etc.
- Have successful track record of creating working Big Data stack that aligned with business needs, and delivered timely enterprise class products
- Experience with delivering and managing scale of Operating Environment
- Experience with Big Data/Micro Service based Systems, SaaS, PaaS, and Architectures
- Experience Developing Systems in Java, Python, Unix
- BSCS, BSEE or equivalent, MSCS preferred
2. Build large datasets that will be used to train the models
3. Empirically evaluate related research works
4. Train and evaluate deep learning architectures on multiple large scale datasets
5. Collaborate with the rest of the research team to produce high-quality research
Job Description :
Sr. Machine Learning Engineer will support our various business vertical teams with insights gained from analyzing company data. The ideal candidate is adept at using large data sets to find opportunities for product and process optimization and using models to test the effectiveness of different courses of action. They must have strong experience using a variety of data mining/data analysis methods, using a variety of data tools, building and implementing models, using/creating algorithms and creating/running simulations. They must have a proven ability to drive business results with their data-based insights. They must be comfortable working with a wide range of stakeholders and functional teams. The right candidate will have a passion for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes.
- Collaborate with product management and engineering departments to understand company needs and devise possible solutions
- Keep up-to-date with latest technology trends
- Communicate results and ideas to key decision makers
- Implement new statistical or other mathematical methodologies as needed for specific models or analysis
- Optimize joint development efforts through appropriate database use and project design
Skills & Requirements :
Technical Skills :
- Demonstrated skill in the use of one or more analytic software tools or languages (e.g., R, Python, Pyomo, Julia/Jump, Matlab, SAS,SQL)
- Demonstrated skill at data cleansing, data quality assessment, and using analytics for data assessment
- End-to-end system design: data analysis, feature engineering, technique selection & implementation, debugging, and maintenance in production.
- Profound understanding of skills like outlier handling, data imputation, bias, variance, cross validation etc.
- Demonstrated skill in modeling techniques, including but not limited to Predictive modeling, Supervised learning, Unsupervised learning, Machine Learning, Statistical Modeling, Natural language processing, Recommendation engines,
- Demonstrated skill in analytic prototyping, analytic scaling, and solutions integration
- Developing hypotheses and set up your own problem frameworks to test for the best solutions
- Knowledge of data visualization tools - ggplot, Dash, d3.js and Matplottlib (or any other data visualization like Tableau, Qlikview)
- Generating insights for a business context
- Experience with cloud technologies for building, deploying and delivering data science applications is desired (preferably in Microsoft Azure)
- Experience in Tensorflow, Keras, Theano, Text Mining is desirable but not mandatory
- Experience to work in Agile and DevOps processes.
Core Skills :
- Bachelor or master degree in information technology, computer science, business administration or a related discipline.
- Certified in Agile Product Owner / SCRUM master and/or other Agile techniques
Leadership Skills :
- Strong stakeholder management and influencing skills. Able to articulate a vision and build support for that vision in the wider team and organization.
- Ability to self-start and direct efforts based on high-level business objectives
- Strong collaboration and leadership skills with the ability to coach and develop teams to meet new challenges.
- Strong interpersonal, communication, facilitation and presentation skills.
- Work through complex interfaces across organizational and geographic boundaries
- Excellent analytical, planning and problem solving skills
Job Experience Requirements :
- Utilize an advanced knowledge level of the Data Science Toolbox to participate in the entire Data Science Project Life cycle and execute end-to-end Data Science project
- Work end-to-end on Data Science developments contributing to all aspects of the project life cycle
- Keep customers as focus of analysis insight and recommendation.
- Help define business objectives/customer needs by capturing the right requirements from the right customers.
- Can take defined problems and identify resolution paths and opportunities to solve them; which you validate by defining hypotheses and driving experiments
- Can identify unstructured problems and articulate opportunities to form new analytics project ideas
- Use and understand the key performance indicators (KPIs) and diagnostics to measure performance against business goals
- Compile integrate and analyze data from multiple sources to identify trends expose new opportunities and answer ongoing business questions
- Execute hypothesis-driven analysis to address business questions issues and opportunities
- Build validate and manage advanced models (e.g. explanatory predictive) using statistical and/or other analytical methods
- Are familiar working within Agile Project Management methodologies / structures
- Analyze results using statistical methods and work with senior team members to make recommendations to improve customer experience and business results
- Have the ability to conceptualize formulate prototype and implement algorithms to capture customer behavior and solve business problems
- Analyze results using statistical methods to make recommendations to improve customer experience and business results
High Level Scope of Work :
- Work with AI / Analytics team to priorities MACHINE LEARNING Identified USE CASES for Development and Rollout
- Meet and understand current retail / Marketing Requirements and how AI/ML solution will address and automate the decision process.
- Develop AI/ML Programs using DATAIKU Solution & Python or open source tech with focus to deliver high Quality and accurate ML prediction Model
- Gather additional and external data sources to support the AI/ML Model as desired .
- Support the ML Model and FINE TUNEit to ensure high accuracy all the time.
- Example of use cases (Customer Segmentation , Product Recommendation, Price Optimization, Retail Customer Personalization Offers, Next Best Location for Business Est, CCTV Computer Vision, NLP and Voice Recognition Solutions)
Required technology expertise :
- Deep Knowledge & Understanding on MACHINE LEARNING ALGORITHMS (Supervised / Unsupervised Learning / Deep Learning Models)
- Hands on EXP for at least 5+ years with PYTHON and R STATISTICS PROGRAMMING Languages
- Strong Database Development knowledge using SQL and PL/SQL
- Must have EXP using Commercial Data Science Solution particularly DATAIKU and (Altryx, SAS, Azure ML, Google ML, Oracle ML is a plus)
- Strong hands on EXP with BIG DATA Solution Architecture and Optimization for AI/ML Workload.
- Data Analytics and BI Tools Hand on EXP particularly (Oracle OBIEE and Power BI)
- Have implemented and Developed at least 3 successful AI/ML Projects with tangible Business Outcomes In retail Focused Industry
- Have at least 5+ Years EXP in Retail Industry and Customer Focus Business.
- Ability to communicate with Business Owner & stakeholders to understand their current issues and provide MACHINE LEARNING Solution accordingly.
- Bachelor Degree or Master Degree in Data Science, Artificial Intelligent, Computer Science
- Certified as DATA SCIENTIST or MACHINE LEARNING Expert.
We’re looking to hire someone to help scale Machine Learning and NLP efforts at Episource. You’ll work with the team that develops the models powering Episource’s product focused on NLP driven medical coding. Some of the problems include improving our ICD code recommendations , clinical named entity recognition and information extraction from clinical notes.
This is a role for highly technical machine learning & data engineers who combine outstanding oral and written communication skills, and the ability to code up prototypes and productionalize using a large range of tools, algorithms, and languages. Most importantly they need to have the ability to autonomously plan and organize their work assignments based on high-level team goals.
You will be responsible for setting an agenda to develop and ship machine learning models that positively impact the business, working with partners across the company including operations and engineering. You will use research results to shape strategy for the company, and help build a foundation of tools and practices used by quantitative staff across the company.
What you will achieve:
Define the research vision for data science, and oversee planning, staffing, and prioritization to make sure the team is advancing that roadmap
Invest in your team’s skills, tools, and processes to improve their velocity, including working with engineering counterparts to shape the roadmap for machine learning needs
Hire, retain, and develop talented and diverse staff through ownership of our data science hiring processes, brand, and functional leadership of data scientists
Evangelise machine learning and AI internally and externally, including attending conferences and being a thought leader in the space
Partner with the executive team and other business leaders to deliver cross-functional research work and models
Strong background in classical machine learning and machine learning deployments is a must and preferably with 4-8 years of experience
Knowledge of deep learning & NLP
Hands-on experience in TensorFlow/PyTorch, Scikit-Learn, Python, Apache Spark & Big Data platforms to manipulate large-scale structured and unstructured datasets.
Experience with GPU computing is a plus.
Professional experience as a data science leader, setting the vision for how to most effectively use data in your organization. This could be through technical leadership with ownership over a research agenda, or developing a team as a personnel manager in a new area at a larger company.
Expert-level experience with a wide range of quantitative methods that can be applied to business problems.
Evidence you’ve successfully been able to scope, deliver and sell your own research in a way that shifts the agenda of a large organization.
Excellent written and verbal communication skills on quantitative topics for a variety of audiences: product managers, designers, engineers, and business leaders.
Fluent in data fundamentals: SQL, data manipulation using a procedural language, statistics, experimentation, and modeling
Professional experience as a data science leader, setting the vision for how to most effectively use data in your organization
Expert-level experience with machine learning that can be applied to business problems
Evidence you’ve successfully been able to scope, deliver and sell your own work in a way that shifts the agenda of a large organization
Fluent in data fundamentals: SQL, data manipulation using a procedural language, statistics, experimentation, and modeling
Degree in a field that has very applicable use of data science / statistics techniques (e.g. statistics, applied math, computer science, OR a science field with direct statistics application)
5+ years of industry experience in data science and machine learning, preferably at a software product company
3+ years of experience managing data science teams, incl. managing/grooming managers beneath you
3+ years of experience partnering with executive staff on data topics