Data Scientist

RESPONSIBILITIES:

 Requirement understanding and elicitation, analyze, data/workflows, contribute to product

project and Proof of concept (POC)

 Contribute to prepare design documents and effort estimations.

 Develop AI/ML Models using best in-class ML models.

 Building, testing, and deploying AI/ML solutions.

 Work with Business Analysts and Product Managers to assist with defining functional user

stories.

 Ensure deliverables across teams are of high quality and clearly documented. 

 Recommend best ML practices/Industry standards for any ML use case.

 Proactively take up R and D and recommend solution options for any ML use case.

REQUIREMENTS:

Required Skills

 Overall experience of 4 to 7 Years working on AI/ML framework development

 Good programming knowledge in Python is must.

 Good Knowledge of R and SAS is desired.

 Good hands on and working knowledge SQL, Data Model, CRISP-DM.

 Proficiency with Uni/multivariate statistics, algorithm design, and predictive AI/ML modelling.

 Strong knowledge of machine learning algorithms, linear regression, logistic regression, KNN,

Random Forest, Support Vector Machines and Natural Language Processing.

 Experience with NLP and deep neural networks using synthetic and artificial data.

 Involved in different phases of SDLC and have good working exposure on different SLDC’s like

Agile Methodologies.

Daily and monthly responsibilities

• Review and coordinate with business application teams on data delivery requirements.
• Develop estimation and proposed delivery schedules in coordination with development team.
• Develop sourcing and data delivery designs.
• Review data model, metadata and delivery criteria for solution.
• Review and coordinate with team on test criteria and performance of testing.
• Contribute to the design, development and completion of project deliverables.
• Complete in-depth data analysis and contribution to strategic efforts
• Complete understanding of how we manage data with focus on improvement of how data is sourced and managed across multiple business areas.

Basic Qualifications

• Bachelor’s degree.
• 5+ years of data analysis working with business data initiatives.
• Knowledge of Structured Query Language (SQL) and use in data access and analysis.
• Proficient in data management including data analytical capability.
• Excellent verbal and written communications also high attention to detail.
• Experience with Python.
• Presentation skills in demonstrating system design and data analysis solutions.

Airflow developer:

Exp: 5 to 10yrs & Relevant exp must be above 4 Years.

Work location: Hyderabad (Hybrid Model)

Job description:  

·        Experience in working on Airflow.

·        Experience in SQL, Python, and Object-oriented programming. 

·        Experience in the data warehouse, database concepts, and ETL tools (Informatica, DataStage, Pentaho, etc.).

·        Azure experience and exposure to Kubernetes. 

·        Experience in Azure data factory, Azure Databricks, and Snowflake. 

Required Skills: Azure Databricks/Data Factory, Kubernetes/Dockers, DAG Development, Hands-on Python coding.

Job Responsibilities:

1. Develop/debug applications using Python.

2. Improve code quality and code coverage for existing or new program.

3. Deploy and Integrate the Machine Learning models.

4. Test and validate the deployments.

5. ML Ops function.

Technical Skills

1. Graduate in Engineering or Technology with strong academic credentials

2. 4 to 8 years of experience as a Python developer.

3. Excellent understanding of SDLC processes

4. Strong knowledge of Unit testing, code quality improvement

5. Cloud based deployment and integration of applications/micro services.

6. Experience with NoSQL databases, such as MongoDB, Cassandra

7. Strong applied statistics skills

8. Knowledge of creating CI/CD pipelines and touchless deployment.

9. Knowledge about API, Data Engineering techniques.

10. AWS

11. Knowledge of Machine Learning and Large Language Model.

Nice to Have

1. Exposure to financial research domain

2. Experience with JIRA, Confluence

3. Understanding of scrum and Agile methodologies

4. Experience with data visualization tools, such as Grafana, GGplot, etc

• Partnering with internal business owners (product, marketing, edit, etc.) to understand needs and develop custom analysis to optimize for user engagement and retention
• Good understanding of the underlying business and workings of cross functional teams for successful execution
• Design and develop analyses based on business requirement needs and challenges.
• Leveraging statistical analysis on consumer research and data mining projects, including segmentation, clustering, factor analysis, multivariate regression, predictive modeling, etc.
• Providing statistical analysis on custom research projects and consult on A/B testing and other statistical analysis as needed. Other reports and custom analysis as required.
• Identify and use appropriate investigative and analytical technologies to interpret and verify results.
• Apply and learn a wide variety of tools and languages to achieve results
• Use best practices to develop statistical and/ or machine learning techniques to build models that address business needs.

• 2 - 4 years  of relevant experience in Data science.
• Preferred education: Bachelor's degree in a technical field or equivalent experience.
• Experience in advanced analytics, model building, statistical modeling, optimization, and machine learning algorithms.
• Machine Learning Algorithms: Crystal clear understanding, coding, implementation, error analysis, model tuning knowledge on Linear Regression, Logistic Regression, SVM, shallow Neural Networks, clustering, Decision Trees, Random forest, XGBoost, Recommender Systems, ARIMA and Anomaly Detection. Feature selection, hyper parameters tuning, model selection and error analysis, boosting and ensemble methods.
• Strong with programming languages like Python and data processing using SQL or equivalent and ability to experiment with newer open source tools.
• Experience in normalizing data to ensure it is homogeneous and consistently formatted to enable sorting, query and analysis.
• Experience designing, developing, implementing and maintaining a database and programs to manage data analysis efforts.
• Experience with big data and cloud computing viz. Spark, Hadoop (MapReduce, PIG, HIVE).
• Experience in risk and credit score domains preferred.

•  Strong problem-solving skills with an emphasis on product development.

• 5+ years of experience in a Data Engineer role
• Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field.
• Experience with big data tools: Hadoop, Spark, Kafka, etc.
• Experience with relational SQL and NoSQL databases such as Cassandra.
• Experience with AWS cloud services: EC2, EMR, Athena
• Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.
• Advanced SQL knowledge and experience working with relational databases, query authoring (SQL) as well as familiarity with unstructured datasets.
• Deep problem-solving skills to perform root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.