o Strong Python development skills, with 7+ yrs. experience with SQL.
o A bachelor or master’s degree in Computer Science or related areas
o 5+ years of experience in data integration and pipeline development
o Experience in Implementing Databricks Delta lake and data lake
o Expertise designing and implementing data pipelines using modern data engineering approach and tools: SQL, Python, Delta Lake, Databricks, Snowflake Spark
o Experience in working with multiple file formats (Parque, Avro, Delta Lake) & API
o experience with AWS Cloud on data integration with S3.
o Hands on Development experience with Python and/or Scala.
o Experience with SQL and NoSQL databases.
o Experience in using data modeling techniques and tools (focused on Dimensional design)
o Experience with micro-service architecture using Docker and Kubernetes
o Have experience working with one or more of the public cloud providers i.e. AWS, Azure or GCP
o Experience in effectively presenting and summarizing complex data to diverse audiences through visualizations and other means
o Excellent verbal and written communications skills and strong leadership capabilities
Skills:
ML
MOdelling
Python
SQL
Azure Data Lake, dataFactory, Databricks, Delta Lake
About CES Information Technologies
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About DeepIntent:
DeepIntent is a marketing technology company that helps healthcare brands strengthen communication with patients and healthcare professionals by enabling highly effective and performant digital advertising campaigns. Our healthcare technology platform, MarketMatch™, connects advertisers, data providers, and publishers to operate the first unified, programmatic marketplace for healthcare marketers. The platform’s built-in identity solution matches digital IDs with clinical, behavioural, and contextual data in real-time so marketers can qualify 1.6M+ verified HCPs and 225M+ patients to find their most clinically-relevant audiences and message them on a one-to-one basis in a privacy-compliant way. Healthcare marketers use MarketMatch to plan, activate, and measure digital campaigns in ways that best suit their business, from managed service engagements to technical integration or self-service solutions. DeepIntent was founded by Memorial Sloan Kettering alumni in 2016 and acquired by Propel Media, Inc. in 2017. We proudly serve major pharmaceutical and Fortune 500 companies out of our offices in New York, Bosnia and India.
What You’ll Do:
- Establish formal data practice for the organisation.
- Build & operate scalable and robust data architectures.
- Create pipelines for the self-service introduction and usage of new data
- Implement DataOps practices
- Design, Develop, and operate Data Pipelines which support Data scientists and machine learning
- Engineers.
- Build simple, highly reliable Data storage, ingestion, and transformation solutions which are easy
- to deploy and manage.
- Collaborate with various business stakeholders, software engineers, machine learning
- engineers, and analysts.
Who You Are:
- Experience in designing, developing and operating configurable Data pipelines serving high
- volume and velocity data.
- Experience working with public clouds like GCP/AWS.
- Good understanding of software engineering, DataOps, data architecture, Agile and
- DevOps methodologies.
- Experience building Data architectures that optimize performance and cost, whether the
- components are prepackaged or homegrown
- Proficient with SQL, Java, Spring boot, Python or JVM-based language, Bash
- Experience with any of Apache open source projects such as Spark, Druid, Beam, Airflow
- etc. and big data databases like BigQuery, Clickhouse, etc
- Good communication skills with the ability to collaborate with both technical and non-technical
- people.
- Ability to Think Big, take bets and innovate, Dive Deep, Bias for Action, Hire and Develop the Best, Learn and be Curious
Job Title -Data Scientist
Job Duties
- Data Scientist responsibilities includes planning projects and building analytics models.
- You should have a strong problem-solving ability and a knack for statistical analysis.
- If you're also able to align our data products with our business goals, we'd like to meet you. Your ultimate goal will be to help improve our products and business decisions by making the most out of our data.
Responsibilities
Own end-to-end business problems and metrics, build and implement ML solutions using cutting-edge technology.
Create scalable solutions to business problems using statistical techniques, machine learning, and NLP.
Design, experiment and evaluate highly innovative models for predictive learning
Work closely with software engineering teams to drive real-time model experiments, implementations, and new feature creations
Establish scalable, efficient, and automated processes for large-scale data analysis, model development, deployment, experimentation, and evaluation.
Research and implement novel machine learning and statistical approaches.
Requirements
2-5 years of experience in data science.
In-depth understanding of modern machine learning techniques and their mathematical underpinnings.
Demonstrated ability to build PoCs for complex, ambiguous problems and scale them up.
Strong programming skills (Python, Java)
High proficiency in at least one of the following broad areas: machine learning, statistical modelling/inference, information retrieval, data mining, NLP
Experience with SQL and NoSQL databases
Strong organizational and leadership skills
Excellent communication skills
Technical Knowledge (Must Have)
- Strong experience in SQL / HiveQL/ AWS Athena,
- Strong expertise in the development of data pipelines (snaplogic is preferred).
- Design, Development, Deployment and administration of data processing applications.
- Good Exposure towards AWS and Azure Cloud computing environments.
- Knowledge around BigData, AWS Cloud Architecture, Best practices, Securities, Governance, Metadata Management, Data Quality etc.
- Data extraction through various firm sources (RDBMS, Unstructured Data Sources) and load to datalake with all best practices.
- Knowledge in Python
- Good knowledge in NoSQL technologies (Neo4J/ MongoDB)
- Experience/knowledge in SnapLogic (ETL Technologies)
- Working knowledge on Unix (AIX, Linux), shell scripting
- Experience/knowledge in Data Modeling. Database Development
- Experience/knowledge creation of reports and dashboards in Tableau/ PowerBI
Duties and Responsibilities:
Research and Develop Innovative Use Cases, Solutions and Quantitative Models
Quantitative Models in Video and Image Recognition and Signal Processing for cloudbloom’s
cross-industry business (e.g., Retail, Energy, Industry, Mobility, Smart Life and
Entertainment).
Design, Implement and Demonstrate Proof-of-Concept and Working Proto-types
Provide R&D support to productize research prototypes.
Explore emerging tools, techniques, and technologies, and work with academia for cutting-
edge solutions.
Collaborate with cross-functional teams and eco-system partners for mutual business benefit.
Team Management Skills
Academic Qualification
7+ years of professional hands-on work experience in data science, statistical modelling, data
engineering, and predictive analytics assignments
Mandatory Requirements: Bachelor’s degree with STEM background (Science, Technology,
Engineering and Management) with strong quantitative flavour
Innovative and creative in data analysis, problem solving and presentation of solutions.
Ability to establish effective cross-functional partnerships and relationships at all levels in a
highly collaborative environment
Strong experience in handling multi-national client engagements
Good verbal, writing & presentation skills
Core Expertise
Excellent understanding of basics in mathematics and statistics (such as differential
equations, linear algebra, matrix, combinatorics, probability, Bayesian statistics, eigen
vectors, Markov models, Fourier analysis).
Building data analytics models using Python, ML libraries, Jupyter/Anaconda and Knowledge
database query languages like SQL
Good knowledge of machine learning methods like k-Nearest Neighbors, Naive Bayes, SVM,
Decision Forests.
Strong Math Skills (Multivariable Calculus and Linear Algebra) - understanding the
fundamentals of Multivariable Calculus and Linear Algebra is important as they form the basis
of a lot of predictive performance or algorithm optimization techniques.
Deep learning : CNN, neural Network, RNN, tensorflow, pytorch, computervision,
Large-scale data extraction/mining, data cleansing, diagnostics, preparation for Modeling
Good applied statistical skills, including knowledge of statistical tests, distributions,
regression, maximum likelihood estimators, Multivariate techniques & predictive modeling
cluster analysis, discriminant analysis, CHAID, logistic & multiple regression analysis
Experience with Data Visualization Tools like Tableau, Power BI, Qlik Sense that help to
visually encode data
Excellent Communication Skills – it is incredibly important to describe findings to a technical
and non-technical audience
Capability for continuous learning and knowledge acquisition.
Mentor colleagues for growth and success
Strong Software Engineering Background
Hands-on experience with data science tools
About us
SteelEye is the only regulatory compliance technology and data analytics firm that offers transaction reporting, record keeping, trade reconstruction, best execution and data insight in one comprehensive solution. The firm’s scalable secure data storage platform offers encryption at rest and in flight and best-in-class analytics to help financial firms meet regulatory obligations and gain competitive advantage.
The company has a highly experienced management team and a strong board, who have decades of technology and management experience and worked in senior positions at many leading international financial businesses. We are a young company that shares a commitment to learning, being smart, working hard and being honest in all we do and striving to do that better each day. We value all our colleagues equally and everyone should feel able to speak up, propose an idea, point out a mistake and feel safe, happy and be themselves at work.
Being part of a start-up can be equally exciting as it is challenging. You will be part of the SteelEye team not just because of your talent but also because of your entrepreneurial flare which we thrive on at SteelEye. This means we want you to be curious, contribute, ask questions and share ideas. We encourage you to get involved in helping shape our business. What you'll do
What you will do?
- Deliver plugins for our python based ETL pipelines.
- Deliver python services for provisioning and managing cloud infrastructure.
- Design, Develop, Unit Test, and Support code in production.
- Deal with challenges associated with large volumes of data.
- Manage expectations with internal stakeholders and context switch between multiple deliverables as priorities change.
- Thrive in an environment that uses AWS and Elasticsearch extensively.
- Keep abreast of technology and contribute to the evolution of the product.
- Champion best practices and provide mentorship.
What we're looking for
- Python 3.
- Python libraries used for data (such as pandas, numpy).
- AWS.
- Elasticsearch.
- Performance tuning.
- Object Oriented Design and Modelling.
- Delivering complex software, ideally in a FinTech setting.
- CI/CD tools.
- Knowledge of design patterns.
- Sharp analytical and problem-solving skills.
- Strong sense of ownership.
- Demonstrable desire to learn and grow.
- Excellent written and oral communication skills.
- Mature collaboration and mentoring abilities.
What will you get?
- This is an individual contributor role. So, if you are someone who loves to code and solve complex problems and build amazing products and not worry about anything else, this is the role for you.
- You will have the chance to learn from the best in the business who have worked across the world and are technology geeks.
- Company that always appreciates ownership and initiative. If you are someone who is full of ideas, this role is for you.
Responsibilities:
- Improve robustness of Leena AI current NLP stack
- Increase zero shot learning capability of Leena AI current NLP stack
- Opportunity to add/build new NLP architectures based on requirements
- Manage End to End lifecycle of the data in the system till it achieves more than 90% accuracy
- Manage a NLP team
Page BreakRequirements:
- Strong understanding of linear algebra, optimisation, probability, statistics
- Experience in the data science methodology from exploratory data analysis, feature engineering, model selection, deployment of the model at scale and model evaluation
- Experience in deploying NLP architectures in production
- Understanding of latest NLP architectures like transformers is good to have
- Experience in adversarial attacks/robustness of DNN is good to have
- Experience with Python Web Framework (Django), Analytics and Machine Learning frameworks like Tensorflow/Keras/Pytorch.
- Focusing on developing new concepts and user experiences through rapid prototyping and collaboration with the best-in-class research and development team.
- Reading research papers and implementing state-of-the-art techniques for computer vision
- Building and managing datasets.
- Providing Rapid experimentation, analysis, and deployment of machine/deep learning models
- Based on requirements set by the team, helping develop new and rapid prototypes
- Developing end to end products for problems related to agritech and other use cases
- Leading the deep learning team
- MS/ME/PhD in Computer Science, Computer Engineering equivalent Proficient in Python and C++, CUDA a plus
- International conference papers/Patents, Algorithm design, deep learning development, programming (Python, C/C++)
- Knowledge of multiple deep-learning frameworks, such as Caffe, TensorFlow, Theano, Torch/PyTorch
- Problem Solving: Deep learning development
- Vision, perception, control, planning algorithm development
- Track record of excellence in the machine learning / perception / control, including patents, publications to international conferences or journals.
- Communications: Good communication skills
Job Description
We are looking for a data scientist that will help us to discover the information hidden in vast amounts of data, and help us make smarter decisions to deliver even better products. Your primary focus will be in applying data mining techniques, doing statistical analysis, and building high quality prediction systems integrated with our products.
Responsibilities
- Selecting features, building and optimizing classifiers using machine learning techniques
- Data mining using state-of-the-art methods
- Extending company’s data with third party sources of information when needed
- Enhancing data collection procedures to include information that is relevant for building analytic systems
- Processing, cleansing, and verifying the integrity of data used for analysis
- Doing ad-hoc analysis and presenting results in a clear manner
- Creating automated anomaly detection systems and constant tracking of its performance
Skills and Qualifications
- Excellent understanding of machine learning techniques and algorithms, such as Linear regression, SVM, Decision Forests, LSTM, CNN etc.
- Experience with Deep Learning preferred.
- Experience with common data science toolkits, such as R, NumPy, MatLab, etc. Excellence in at least one of these is highly desirable
- Great communication skills
- Proficiency in using query languages such as SQL, Hive, Pig
- Good applied statistics skills, such as statistical testing, regression, etc.
- Good scripting and programming skills
- Data-oriented personality
DataWeave provides Retailers and Brands with “Competitive Intelligence as a Service” that enables them to take key decisions that impact their revenue. Powered by AI, we provide easily consumable and actionable competitive intelligence by aggregating and analyzing billions of publicly available data points on the Web to help businesses develop data-driven strategies and make smarter decisions.
Data Science@DataWeave
We the Data Science team at DataWeave (called Semantics internally) build the core machine learning backend and structured domain knowledge needed to deliver insights through our data products. Our underpinnings are: innovation, business awareness, long term thinking, and pushing the envelope. We are a fast paced labs within the org applying the latest research in Computer Vision, Natural Language Processing, and Deep Learning to hard problems in different domains.
How we work?
It's hard to tell what we love more, problems or solutions! Every day, we choose to address some of the hardest data problems that there are. We are in the business of making sense of messy public data on the web. At serious scale!
What do we offer?
- Some of the most challenging research problems in NLP and Computer Vision. Huge text and image datasets that you can play with!
- Ability to see the impact of your work and the value you're adding to our customers almost immediately.
- Opportunity to work on different problems and explore a wide variety of tools to figure out what really excites you.
- A culture of openness. Fun work environment. A flat hierarchy. Organization wide visibility. Flexible working hours.
- Learning opportunities with courses and tech conferences. Mentorship from seniors in the team.
- Last but not the least, competitive salary packages and fast paced growth opportunities.
Who are we looking for?
The ideal candidate is a strong software developer or a researcher with experience building and shipping production grade data science applications at scale. Such a candidate has keen interest in liaising with the business and product teams to understand a business problem, and translate that into a data science problem. You are also expected to develop capabilities that open up new business productization opportunities.
We are looking for someone with 6+ years of relevant experience working on problems in NLP or Computer Vision with a Master's degree (PhD preferred).
Key problem areas
- Preprocessing and feature extraction noisy and unstructured data -- both text as well as images.
- Keyphrase extraction, sequence labeling, entity relationship mining from texts in different domains.
- Document clustering, attribute tagging, data normalization, classification, summarization, sentiment analysis.
- Image based clustering and classification, segmentation, object detection, extracting text from images, generative models, recommender systems.
- Ensemble approaches for all the above problems using multiple text and image based techniques.
Relevant set of skills
- Have a strong grasp of concepts in computer science, probability and statistics, linear algebra, calculus, optimization, algorithms and complexity.
- Background in one or more of information retrieval, data mining, statistical techniques, natural language processing, and computer vision.
- Excellent coding skills on multiple programming languages with experience building production grade systems. Prior experience with Python is a bonus.
- Experience building and shipping machine learning models that solve real world engineering problems. Prior experience with deep learning is a bonus.
- Experience building robust clustering and classification models on unstructured data (text, images, etc). Experience working with Retail domain data is a bonus.
- Ability to process noisy and unstructured data to enrich it and extract meaningful relationships.
- Experience working with a variety of tools and libraries for machine learning and visualization, including numpy, matplotlib, scikit-learn, Keras, PyTorch, Tensorflow.
- Use the command line like a pro. Be proficient in Git and other essential software development tools.
- Working knowledge of large-scale computational models such as MapReduce and Spark is a bonus.
- Be a self-starter—someone who thrives in fast paced environments with minimal ‘management’.
- It's a huge bonus if you have some personal projects (including open source contributions) that you work on during your spare time. Show off some of your projects you have hosted on GitHub.
Role and responsibilities
- Understand the business problems we are solving. Build data science capability that align with our product strategy.
- Conduct research. Do experiments. Quickly build throw away prototypes to solve problems pertaining to the Retail domain.
- Build robust clustering and classification models in an iterative manner that can be used in production.
- Constantly think scale, think automation. Measure everything. Optimize proactively.
- Take end to end ownership of the projects you are working on. Work with minimal supervision.
- Help scale our delivery, customer success, and data quality teams with constant algorithmic improvements and automation.
- Take initiatives to build new capabilities. Develop business awareness. Explore productization opportunities.
- Be a tech thought leader. Add passion and vibrance to the team. Push the envelope. Be a mentor to junior members of the team.
- Stay on top of latest research in deep learning, NLP, Computer Vision, and other relevant areas.