Syntasa Hiring Drive 2024: Syntasa Hiring Drive 2024 for its Data Scientist Syntasa Drive organizes off-campus drives for candidates in any batch. To apply, candidates should have a bachelor’s degree. if you are interested, please apply as soon as possible.
Company Name: Syntasa
Role: Data Scientist
Location: Remote
Experience: 2 years
Qualification: Bachelor’s degree
Batch: Any
Job Type: Full Time
Salary: 13 LPA (Expected)
Syntasa Hiring Drive 2024
Job Description:
- As a data scientist within our delivery team, you will be leveraging a multitude of big data, ML and statistical methods to help our customers realize the potential of modern data science and data-driven approaches.
- You will be working from an end-to-end basis by building the data pipelines needed for your models, building/optimizing the models and enabling your data driven outputs to be leveraged by both stakeholders and downstream applications.
- We work across several public sector and commercial clients, thus allowing your data expertise to help facilitate positive outcomes across a broad range of sectors.
- Join our team of leading data engineers, machine learning researchers, and data scientists who are building the next generation of AI Customer Assisted Analytics technology.
- Syntasa leverages proven streaming, machine learning, visualization, and big data technologies to process billions of records in real-time, resulting in actionable intelligence that improves acquisition, conversion, and retention.
- This provides a unique opportunity to be a part of a growing team in a fast-paced and evolving environment that delivers business impacts from data-driven recommendations.
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Requirements:
- At least 2 years experience in an analytical role as a data scientist, analyst or machine learning engineer
- An ability to work with data using SQL and tools for statistical analysis (eg. Python, R)
- Solid knowledge of statistics and probability, with demonstrated experience applying these techniques to commercial use cases such as ML models and A/B tests
- Demonstrated experience of developing, deploying and maintaining ML models and data pipelines within a commercial setting.
- Demonstrated experience of translating business and/or project requirements into insights, models and data products that generated tangible business value.
- An ability to work effectively in a team setting and familiarity with commercial collaboration tools such as JIRA, Confluence,
- A strong communicator able to present data driven insights to non-technical stakeholders while also having fruitful conversations with engineering teams
- Curiosity and attention to detail with regards to data quality, distributions, biases and governance.
- An ability to work effectively within a fast paced and dynamic environment.
- An awareness and keen interest in the latest trends / techniques within data, machine learning and AI.
- demonstrable experience implementing models (both pre-built and custom) for NLP, imagery analaysis, topic modelling etc..
- Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc.
- Good applied statistics skills, such as distributions, statistical testing, regression, etc..
- Experience with cloud solution providers such as GCP, AWS and Azure
- Prior experience building robust and reusable code
- Prior experience using notebooking technologies such as Jupyter/Colab notebooks.
- Knowledge of NLP and Image processing algorithms.
- Prior experience with REST APIs
- An understanding of version control, modularity and maintaining code within a production setting.
- An understanding of the web analytics and digital marketing ecosystem (eg. Adobe, Salesforce, Google)
- Prior experience working with DMPs and CDPs
- Prior consulting experience
Skills:
- Fluent in Python/Scala/R as well as SQL/NOSQL with demonstrable experience.
- Experience with Apache Spark
- or other Big Data tools like Apache Flink/MapReduce
- Familiar with Big Data tools such as EMR/ Dataproc /Cloudera/Hortonworks
- Familiar with orchestration tools such as Airflow/DBT/NiFi
- Experience with LLM’s and GPT models a plus.
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