Data Engineer

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

Objective

Data Engineer will be responsible for expanding and optimizing our data and database architecture, as well as optimizing data flow and collection for cross functional teams. The ideal candidate is an experienced data pipeline builder and data wrangler who enjoys optimizing data systems and building. The Data Engineer 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. They must be self-directed and comfortable supporting the data needs of multiple teams, systems, and products

Roles and Responsibilities:

• Should be comfortable in building and optimizing performant data pipelines which include data ingestion, data cleansing and curation into a data warehouse, database, or any other data platform using DASK/Spark.
• Experience in distributed computing environment and Spark/DASK architecture.
• Optimize performance for data access requirements by choosing the appropriate file formats (AVRO, Parquet, ORC etc) and compression codec respectively.
• Experience in writing production ready code in Python and test, participate in code reviews to maintain and improve code quality, stability, and supportability.
• Experience in designing data warehouse/data mart.
• Experience with any RDBMS preferably SQL Server and must be able to write complex SQL queries.
• Expertise in requirement gathering, technical design and functional documents.
• Experience in Agile/Scrum practices.
• Experience in leading other developers and guiding them technically.
• Experience in deploying data pipelines using automated CI/CD approach.
• Ability to write modularized reusable code components.
• Proficient in identifying data issues and anomalies during analysis.
• Strong analytical and logical skills.
• Must be able to comfortably tackle new challenges and learn.
• Must have strong verbal and written communication skills.

Required skills:

• Knowledge on GCP
• Expertise in Google BigQuery
• Expertise in Airflow
• Good Hands on SQL
• Data warehousing concepts

• 3+ years of Experience majoring in applying AI/ML/ NLP / deep learning / data-driven statistical analysis & modelling solutions.
• Programming skills in Python, knowledge in Statistics.
• Hands-on experience developing supervised and unsupervised machine learning algorithms (regression, decision trees/random forest, neural networks, feature selection/reduction, clustering, parameter tuning, etc.). Familiarity with reinforcement learning is highly desirable.
• Experience in the financial domain and familiarity with financial models are highly desirable.
• Experience in image processing and computer vision.
• Experience working with building data pipelines.
• Good understanding of Data preparation, Model planning, Model training, Model validation, Model deployment and performance tuning.
• Should have hands on experience with some of these methods: Regression, Decision Trees,CART, Random Forest, Boosting, Evolutionary Programming, Neural Networks, Support Vector Machines, Ensemble Methods, Association Rules, Principal Component Analysis, Clustering, ArtificiAl Intelligence
• Should have experience in using larger data sets using Postgres Database. 

Senior Data Scientist-Job Description

The Senior Data Scientist role is a creative problem solver who utilizes statistical/mathematical principles and modelling skills to uncover new insights that will significantly and meaningfully impact business decisions and actions.  She/he applies their data science expertise in identifying, defining, and executing state-of-art techniques for academic opportunities and business objectives in collaboration with other Analytics team members. The Senior Data Scientist will execute analyses & outputs spanning test design and measurement, predictive analytics, multivariate analysis, data/text mining, pattern recognition, artificial intelligence, and machine learning.

Key Responsibilities:

• Perform the full range of data science activities including test design and measurement, predictive/advanced analytics, and data mining, and analytic dashboards.
• Extract, manipulate, analyse & interpret data from various corporate data sources developing advanced analytic solutions, deriving key observations, findings, insights, and formulating actionable recommendations.
• Generate clearly understood and intuitive data science / advanced analytics outputs.
• Provide thought leadership and recommendations on business process improvement, analytic solutions to complex problems.
• Participate in best practice sharing and communication platform for advancement of the data science discipline.
• Coach and collaborate with other data scientists and data analysts.
• Present impact, insights, outcomes & recommendations to key business partners and stakeholders.
• Comply with established Service Level Agreements to ensure timely, high quality deliverables with value-add recommendations, clearly articulated key findings and observations.

Qualification:

• Bachelor's Degree (B.A./B.S.) or Master’s Degree (M.A./M.S.) in Computer Science, Statistics, Mathematics, Machine Learning, Physics, or similar degree
• 5+ years of experience in data science in a digitally advanced industry focusing on strategic initiatives, marketing and/or operations.
• Advanced knowledge of best-in-class analytic software tools and languages: Python, SQL, R, SAS, Tableau, Excel, PowerPoint.
• Expertise in statistical methods, statistical analysis, data visualization, and data mining techniques.
• Experience in Test design, Design of Experiments, A/B Testing, Measurement Science Strong influencing skills to drive a robust testing agenda and data driven decision making for process improvements
• Strong Critical thinking skills to track down complex data and engineering issues, evaluate different algorithmic approaches, and analyse data to solve problems.
• Experience in partnering with IT, marketing operations & business operations to deploy predictive analytic solutions.
• Ability to translate/communicate complex analytical/statistical/mathematical concepts with non-technical audience.
• Strong written and verbal communications skills, as well as presentation skills.

• Total Experience of 7-10 years and should be interested in teaching and research
• 3+ years’ experience in data engineering which includes data ingestion, preparation, provisioning, automated testing, and quality checks.
• 3+ Hands-on experience in Big Data cloud platforms like AWS and GCP, Data Lakes and Data Warehouses
• 3+ years of Big Data and Analytics Technologies. Experience in SQL, writing code in spark engine using python, scala or java Language. Experience in Spark, Scala
• Experience in designing, building, and maintaining ETL systems
• Experience in data pipeline and workflow management tools like Airflow
• Application Development background along with knowledge of Analytics libraries, opensource Natural Language Processing, statistical and big data computing libraries
• Familiarity with Visualization and Reporting Tools like Tableau, Kibana.
• Should be good at storytelling in Technology

Who we look for

• Strong technical expertise and building ability 
• Ability to envisage how your technical knowledge could be applied outside of academia - with a focus on impact/disruption
• Ability to explain and articulate complex ideas, simply
• Ability to digest difficult questions/information