11+ GLM Jobs in India
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Advanced degree in computer science, math, statistics or a related discipline ( Must have master degree )
Extensive data modeling and data architecture skills
Programming experience in Python, R
Background in machine learning frameworks such as TensorFlow or Keras
Knowledge of Hadoop or another distributed computing systems
Experience working in an Agile environment
Advanced math skills (Linear algebra
Discrete math
Differential equations (ODEs and numerical)
Theory of statistics 1
Numerical analysis 1 (numerical linear algebra) and 2 (quadrature)
Abstract algebra
Number theory
Real analysis
Complex analysis
Intermediate analysis (point set topology)) ( important )
Strong written and verbal communications
Hands on experience on NLP and NLG
Experience in advanced statistical techniques and concepts. ( GLM/regression, Random forest, boosting, trees, text mining ) and experience with application.
Data Scientist-
We are looking for an experienced Data Scientists to join our engineering team and
help us enhance our mobile application with data. In this role, we're looking for
people who are passionate about developing ML/AI in various domains that solves
enterprise problems. We are keen on hiring someone who loves working in fast paced start-up environment and looking to solve some challenging engineering
problems.
As one of the earliest members in engineering, you will have the flexibility to design
the models and architecture from ground up. As any early-stage start-up, we expect
you to be comfortable wearing various hats, and be proactive contributor in building
something truly remarkable.
Responsibilities
Researches, develops and maintains machine learning and statistical models for
business requirements
Work across the spectrum of statistical modelling including supervised,
unsupervised, & deep learning techniques to apply the right level of solution to
the right problem Coordinate with different functional teams to monitor outcomes and refine/
improve the machine learning models Implements models to uncover patterns and predictions creating business value and innovation
Identify unexplored data opportunities for the business to unlock and maximize
the potential of digital data within the organization
Develop NLP concepts and algorithms to classify and summarize structured/unstructured text data
Qualifications
3+ years of experience solving complex business problems using machine
learning.
Fluency in programming languages such as Python, NLP and Bert, is a must
Strong analytical and critical thinking skills
Experience in building production quality models using state-of-the-art technologies
Familiarity with databases like MySQL, Oracle, SQL Server, NoSQL, etc. is
desirable Ability to collaborate on projects and work independently when required.
Previous experience in Fintech/payments domain is a bonus
You should have Bachelor’s or Master’s degree in Computer Science, Statistics
or Mathematics or another quantitative field from a top tier Institute
We are looking for a Machine Learning engineer for on of our premium client.
Experience: 2-9 years
Location: Gurgaon/Bangalore
Tech Stack:
Python, PySpark, the Python Scientific Stack; MLFlow, Grafana, Prometheus for machine learning pipeline management and monitoring; SQL, Airflow, Databricks, our own open-source data pipelining framework called Kedro, Dask/RAPIDS; Django, GraphQL and ReactJS for horizontal product development; container technologies such as Docker and Kubernetes, CircleCI/Jenkins for CI/CD, cloud solutions such as AWS, GCP, and Azure as well as Terraform and Cloudformation for deployment
Key deliverables for the Data Science Engineer would be to help us 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 on applying data mining techniques, doing statistical analysis, and building high-quality prediction systems integrated with our products.
What will you do?
- You will be building and deploying ML models to solve specific business problems related to NLP, computer vision, and fraud detection.
- You will be constantly assessing and improving the model using techniques like Transfer learning
- You will identify valuable data sources and automate collection processes along with undertaking pre-processing of structured and unstructured data
- You will own the complete ML pipeline - data gathering/labeling, cleaning, storage, modeling, training/testing, and deployment.
- Assessing the effectiveness and accuracy of new data sources and data gathering techniques.
- Building predictive models and machine-learning algorithms to apply to data sets.
- Coordinate with different functional teams to implement models and monitor outcomes.
- Presenting information using data visualization techniques and proposing solutions and strategies to business challenges
We would love to hear from you if :
- You have 2+ years of experience as a software engineer at a SaaS or technology company
- Demonstrable hands-on programming experience with Python/R Data Science Stack
- Ability to design and implement workflows of Linear and Logistic Regression, Ensemble Models (Random Forest, Boosting) using R/Python
- Familiarity with Big Data Platforms (Databricks, Hadoop, Hive), AWS Services (AWS, Sagemaker, IAM, S3, Lambda Functions, Redshift, Elasticsearch)
- Experience in Probability and Statistics, ability to use ideas of Data Distributions, Hypothesis Testing and other Statistical Tests.
- Demonstrable competency in Data Visualisation using the Python/R Data Science Stack.
- Preferable Experience Experienced in web crawling and data scraping
- Strong experience in NLP. Worked on libraries such as NLTK, Spacy, Pattern, Gensim etc.
- Experience with text mining, pattern matching and fuzzy matching
Why Tartan?
- Brand new Macbook
- Stock Options
- Health Insurance
- Unlimited Sick Leaves
- Passion Fund (Invest in yourself or your passion project)
- Wind Down
Knowledge of Hadoop ecosystem installation, initial-configuration and performance tuning.
Expert with Apache Ambari, Spark, Unix Shell scripting, Kubernetes and Docker
Knowledge on python would be desirable.
Experience with HDP Manager/clients and various dashboards.
Understanding on Hadoop Security (Kerberos, Ranger and Knox) and encryption and Data masking.
Experience with automation/configuration management using Chef, Ansible or an equivalent.
Strong experience with any Linux distribution.
Basic understanding of network technologies, CPU, memory and storage.
Database administration a plus.
Qualifications and Education Requirements
2 to 4 years of experience with and detailed knowledge of Core Hadoop Components solutions and
dashboards running on Big Data technologies such as Hadoop/Spark.
Bachelor degree or equivalent in Computer Science or Information Technology or related fields.
datasets
● Translate complex business requirements into scalable technical solutions meeting data design
standards. Strong understanding of analytics needs and proactive-ness to build generic solutions
to improve the efficiency
● Build dashboards using Self-Service tools on Kibana and perform data analysis to support
business verticals
● Collaborate with multiple cross-functional teams and work
We are looking for a savvy Data Engineer to join our growing team of analytics experts.
The hire will be responsible for:
- Expanding and optimizing our data and data pipeline architecture
- Optimizing data flow and collection for cross functional teams.
- Will support our software developers, database architects, data analysts and data scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects.
- Must be self-directed and comfortable supporting the data needs of multiple teams, systems and products.
- Experience with Azure : ADLS, Databricks, Stream Analytics, SQL DW, COSMOS DB, Analysis Services, Azure Functions, Serverless Architecture, ARM Templates
- Experience with relational SQL and NoSQL databases, including Postgres and Cassandra.
- Experience with object-oriented/object function scripting languages: Python, SQL, Scala, Spark-SQL etc.
Nice to have experience with :
- Big data tools: Hadoop, Spark and Kafka
- Data pipeline and workflow management tools: Azkaban, Luigi, Airflow
- Stream-processing systems: Storm
Database : SQL DB
Programming languages : PL/SQL, Spark SQL
Looking for candidates with Data Warehousing experience, strong domain knowledge & experience working as a Technical lead.
The right candidate will be excited by the prospect of optimizing or even re-designing our company's data architecture to support our next generation of products and data initiatives.
at Artivatic
To be considered as a candidate for a Senior Data Engineer position, a person must have a proven track record of architecting data solutions on current and advanced technical platforms. They must have leadership abilities to lead a team providing data centric solutions with best practices and modern technologies in mind. They look to build collaborative relationships across all levels of the business and the IT organization. They possess analytic and problem-solving skills and have the ability to research and provide appropriate guidance for synthesizing complex information and extract business value. Have the intellectual curiosity and ability to deliver solutions with creativity and quality. Effectively work with business and customers to obtain business value for the requested work. Able to communicate technical results to both technical and non-technical users using effective story telling techniques and visualizations. Demonstrated ability to perform high quality work with innovation both independently and collaboratively.