BOLD is seeking for newest addition to our existing Data Science team, you’ll combine your analytical skills and business knowledge to deliver key insights to our Product and Management teams. You’ll help drive product development using our vast user data sets to enhance our current products and to help us find inferences and relationships in this data to build new products – More towards the role required

ABOUT THIS TEAM

The Data Science department at BOLD is responsible for discovering patterns and trends in datasets to get insights, creating predictive algorithms and data models, improving the quality of data or product offerings by utilizing machine learning techniques, distributing suggestions to other teams and top management, and using data tools such as Python and SQL.

The Data Science team actively collaborates with other vertical teams such as Engineering, Portals, BI, Product, Legal. Most of the projects are focused around problems that require a mix of natural language processing and machine learning. Some of the active projects are resume parsing, ranking, summary generation, data quality and scoring, content generation, job recommendations, and conversion analysis. Apart from the business initiatives, the team also explores state of the art methods and keeps them upto to date with technology.

WHAT YOU’LL DO 

• Demonstrate ability to work on data science projects involving predictive modelling, NLP, statistical analysis, vector space modelling, machine learning etc. 
• Leverage our rich data sets of user data to perform research, develop models and create data products with our Development & Product teams 
• Develop novel and scalable data systems in cooperation with our system architects that leverage datasets using machine learning techniques to enhance the user experience 

WHAT YOU’LL NEED 

• Knowledge and experience using statistical and machine learning algorithms including regression, instance-based learning, decision trees, Bayesian statistics, clustering, neural networks, deep learning, ensemble methods 
• Expert knowledge in Python.  
• Practical LLM/RAG experience for search quality  such as  query understanding, semantic retrieval, reranker design .  
• Experience with frameworks that optimizes prompt engineering (langChain/crewai/etc) 
• Experience with Solr/OpenSearch/Elasticsearch … 
• Experience with embedding & vector search  
• Should have done one or more projects involving fine-tuning with LLMs 
• Experience in feature selection, building and optimising classifiers. 
• Experience working with backend technologies such as Flask/ Gunicorn etc. 
• Experience on working with open source library such Spacy,NLTK,Gensim etc  
• Experience on working with deep-learning library such as Tensor flow, Pytorch etc  
• Experience with software stack components including common programming languages, back-end technologies, database modelling, continuous integration, services oriented architecture, software testability etc. 
• Be a keen learner and enthusiastic about developing software.    

EXPERIENCE- 

• Software Engineer- 2.5 years+
• Senior Software Engineer-4.5 years+

#LI-SV1

BOLD is seeking for newest addition to our existing Data Science team, you’ll combine your analytical skills and business knowledge to deliver key insights to our Product and Management teams. You’ll help drive product development using our vast user data sets to enhance our current products and to help us find inferences and relationships in this data to build new products – More towards the role required

ABOUT THIS TEAM

The Data Science department at BOLD is responsible for discovering patterns and trends in datasets to get insights, creating predictive algorithms and data models, improving the quality of data or product offerings by utilizing machine learning techniques, distributing suggestions to other teams and top management, and using data tools such as Python and SQL.

The Data Science team actively collaborates with other vertical teams such as Engineering, Portals, BI, Product, Legal. Most of the projects are focused around problems that require a mix of natural language processing and machine learning. Some of the active projects are resume parsing, ranking, summary generation, data quality and scoring, content generation, job recommendations, and conversion analysis. Apart from the business initiatives, the team also explores state of the art methods and keeps them upto to date with technology.

WHAT YOU’LL DO 

• Demonstrate ability to work on data science projects involving NLP, large language models, predictive modelling, statistical analysis, vector space modelling, machine learning etc. 
• Leverage our rich data sets of user data to perform research, develop models and create data products with our Development & Product teams 
• Develop novel and scalable data systems in cooperation with our system architects that leverage datasets using machine learning techniques to enhance the user experience 
• Collaborates effectively with cross functional teams to deliver end-to-end products & features. 
• Demonstrates ability to multi-task and re-prioritize responsibilities based on changing requirements. 
• Estimates efforts, identify risks, devises and meets project schedules. 
• Runs review meetings effectively and drive the closure of all open issues on time 
• Mentors/coaches data scientists to facilitate their development and provide technical leadership to them. 
• Rises above detail to see broader issues and implications for whole product/team. 

WHAT YOU’LL NEED

• Knowledge and experience using statistical and machine learning algorithms including regression, instance-based learning, decision trees, Bayesian statistics, clustering, neural networks, deep learning, ensemble methods 
• Expert knowledge in Python.  
• Practical LLM/RAG experience for search quality  such as  query understanding, semantic retrieval, reranker design. 
• Experience with Solr/OpenSearch/Elasticsearch .
• Experience with frameworks that optimizes prompt engineering (langChain/crewai/etc) 
• Experience with embedding & vector search  
• Experience in using large language models. 
• Experience in feature selection, building and optimising classifiers. 
• Experience working with backend technologies such as Flask/ Gunicorn etc. 
• Experience on working with open source library such Spacy,NLTK,Gensim etc  
• Experience on working with deep-learning library such as Tensor flow, Pytorch etc  
• Experience with software stack components including common programming languages, back-end technologies, database modelling, continuous integration, services oriented architecture, software testability etc. 
• Be a keen learner and enthusiastic about developing software.  

EXPERIENCE- 

• Module Lead, Data Science- 5.5 years

#LI-SV1

Responsibilities:
○ Design and develop new software applications from scratch
○ Work with developers and other teams across the company to build new features and tools.
○ Add new product features using Python language.
○ Write code which is micro services complaint and can be reused.
○ Own problems end-to-end, thinking through everything from user experience, data models, scalability, operability and ongoing metrics.
○ Uphold our high engineering standards and bring consistency to the codebases, infrastructure, and processes you will encounter.
○ Test and debug code, Monitor and troubleshoot production issues
○ Collaborate with experts in product, design, and operations.
○ Proactive and prompt analysis and identification of functional bugs and performance issues

Requirements:
○ Enjoy being a generalist, working on both the frontend, backend, and everything in between to tackle problems and delight customers.
○ Thinking about tools and services, and writing high quality code.
○ We write code using Python, React and other languages like javascript, typescript, nodejs, shell scripts, AWS cloud services.
○ We use productivity enhancement tools like copilot, cursor etc.
○ Strong knowledge of Databases (either NoSql or RDBMS), DynamoDB and postgres preferred.
○ Strong experience with REST API development, Flask API, and JSON handling.
○ Hands-on experience with Python frameworks or libraries (any of the following is a plus): PySpark, Pandas, NumPy, asyncio, etc.
○ Exposure to ML / GenAI workflows is a strong advantage (model integration, vector DBs, embeddings pipelines, etc.)
○ Unit testing of REST API and server side components on Python
○ Working on CI/CD pipeline.
○ Server caching optimisations using memcache, etc
○ Authentication mechanisms like SAML SSO, MFA, etc
○ If you have worked on Integrations across various systems using APIs or messages that experience will be good to have.
○ Taking pride in working on projects to successful completion, involving a wide variety of technologies and systems.
○ Putting yourself in the shoes of your users, and creating an intuitive, delightful experience.
○ You should have understanding around Security for Web Applications and backend processes. Security is very important for us.
○ Holding yourself and others to a high bar when working with production systems.
○ Stitching many different services and processes together, even if you have not worked with them before.
○ Strong understanding of front-end and back-end technologies
○ Experience working in an agile development environment
○ Knowledge of nodejs is nice-to-have, however not a must.

Experience
○ 4-7 years experience in the IT/Technology industry.
○ 4+ years of experience in Python
○ 3+ years of experience in NoSql / RDBMS, DynamoDB and postgres preferred.
○ 3+ years of experience in working on code version source control tools like Git
○ Experience in sonarqube, use of copilot or similar productivity enhancement tools

Engineering at Enboarder:
○ We work in an environment where it matters to make the right design decisions the first time, and as a result, take on less technical debt.
○ We roll out code to production every 2 weeks.
○ We’re big fans of micro services architecture and are moving a lot of products towards micro services.
○ We like to experiment with new features and do not see failures as bad, but building blocks for future features.
○ We use AWS as our Infrastructure and continually improve. We provide ample opportunities to learn and use new AWS features.
○ Product is a highly collaborative initiative across multiple teams. Engineers are expected to understand and have product input, designing systems towards our long-term product vision.
○ Our customers are fine with fewer features, but are not ok with broken features.
○ People have a strong sense of ownership and accountability for what they’re building.
○ What we build today will be the foundation for other systems in the future.
○ We are very frank on discussing technical matters. If one disagrees with how things are being done, we encourage them to speak up and help us get to the truth faster.

*NOTE:* Hybrid work with 3 days in office.