Data Scientist

Senior Executive - Analytics

Overview of job :-

Our Client is the world’s largest media investment company which is a part of WPP. They are a global digital transformation agency with 1200 employees across 21 nations. Our team of experts support clients in programmatic, social, paid search, analytics, technology, organic search, affiliate marketing, e-commerce and across traditional channels.

We are currently looking for a Sr Executive – Analytics to join us. In this role, you will be responsible for a massive opportunity to build and be a part of largest performance marketing setup APAC is committed to fostering a culture of diversity and inclusion. Our people are our strength so we respect and nurture their individual talent and potential.

Reporting of the role - This role reports to the Director - Analytics,

3 best things about the job:

1. Responsible for data & analytics projects and developing data strategies by diving into data and extrapolating insights and providing guidance to clients

2. Build and be a part of a dynamic team

3. Being part of a global organisations with rapid growth opportunities

Responsibilities of the role:

 Build Marketing-Mix and Multi-Touch attribution models using a range of tools, including free and paid.

 Work with large data sets via hands-on data processing to produce structured data sets for analysis.

 Design and build Visualization, Dashboard and reports for both Internal and external clients using Tableau, Power BI, Datorama or R Shiny/Python.

What you will need:

 Degree in Mathematics, Statistics, Economics, Engineering, Data Science, Computer Science or quantitative field.

 2-3 years’ experience in Marketing/Data Analytics or related field with hands-on experience in building Marketing-Mix and Attribution models.  Proficiency in one or more coding languages – preferred languages: Python, R

 Proficiency in one or more Visualization Tools – Tableau, Datorama, Power BI

 Proficiency in using SQL.

 Proficiency with one or more statistical tools is a plus – Example: SPSS, SAS, MATLAB, Mathcad.

 Working experience using big data technologies (Hive/Hadoop) is a plus

Job Responsibilities

• Design, build & test ETL processes using Python & SQL for the corporate data warehouse
• Inform, influence, support, and execute our product decisions
• Maintain advertising data integrity by working closely with R&D to organize and store data in a format that provides accurate data and allows the business to quickly identify issues.
• Evaluate and prototype new technologies in the area of data processing
• Think quickly, communicate clearly and work collaboratively with product, data, engineering, QA and operations teams
• High energy level, strong team player and good work ethic
• Data analysis, understanding of business requirements and translation into logical pipelines & processes
• Identification, analysis & resolution of production & development bugs
• Support the release process including completing & reviewing documentation
• Configure data mappings & transformations to orchestrate data integration & validation
• Provide subject matter expertise
• Document solutions, tools & processes
• Create & support test plans with hands-on testing
• Peer reviews of work developed by other data engineers within the team
• Establish good working relationships & communication channels with relevant departments

Skills and Qualifications we look for

• University degree 2.1 or higher (or equivalent) in a relevant subject. Master’s degree in any data subject will be a strong advantage.
• 4 - 6 years experience with data engineering.
• Strong coding ability and software development experience in Python.
• Strong hands-on experience with SQL and Data Processing.
• Google cloud platform (Cloud composer, Dataflow, Cloud function, Bigquery, Cloud storage, dataproc)
• Good working experience in any one of the ETL tools (Airflow would be preferable).
• Should possess strong analytical and problem solving skills.
• Good to have skills - Apache pyspark, CircleCI, Terraform
• Motivated, self-directed, able to work with ambiguity and interested in emerging technologies, agile and collaborative processes.
• Understanding & experience of agile / scrum delivery methodology

About Quadratyx:

We are a product-centric insight & automation services company globally. We help the world’s organizations make better & faster decisions using the power of insight & intelligent automation. We build and operationalize their next-gen strategy, through Big Data, Artificial Intelligence, Machine Learning, Unstructured Data Processing and Advanced Analytics. Quadratyx can boast more extensive experience in data sciences & analytics than most other companies in India.

We firmly believe in Excellence Everywhere.

Job Description

Purpose of the Job/ Role:

• As a Technical Lead, your work is a combination of hands-on contribution, customer engagement and technical team management. Overall, you’ll design, architect, deploy and maintain big data solutions.

Key Requisites:

• Expertise in Data structures and algorithms.

• Technical management across the full life cycle of big data (Hadoop) projects from requirement gathering and analysis to platform selection, design of the architecture and deployment.

• Scaling of cloud-based infrastructure.

• Collaborating with business consultants, data scientists, engineers and developers to develop data solutions.

• Led and mentored a team of data engineers.

• Hands-on experience in test-driven development (TDD).

• Expertise in No SQL like Mongo, Cassandra etc, preferred Mongo and strong knowledge of relational databases.

• Good knowledge of Kafka and Spark Streaming internal architecture.

• Good knowledge of any Application Servers.

• Extensive knowledge of big data platforms like Hadoop; Hortonworks etc.

• Knowledge of data ingestion and integration on cloud services such as AWS; Google Cloud; Azure etc. 

Skills/ Competencies Required

Technical Skills

• Strong expertise (9 or more out of 10) in at least one modern programming language, like Python, or Java.

• Clear end-to-end experience in designing, programming, and implementing large software systems.

• Passion and analytical abilities to solve complex problems Soft Skills.

• Always speaking your mind freely.

• Communicating ideas clearly in talking and writing, integrity to never copy or plagiarize intellectual property of others.

• Exercising discretion and independent judgment where needed in performing duties; not needing micro-management, maintaining high professional standards.

Academic Qualifications & Experience Required

Required Educational Qualification & Relevant Experience

• Bachelor’s or Master’s in Computer Science, Computer Engineering, or related discipline from a well-known institute.

• Minimum 7 - 10 years of work experience as a developer in an IT organization (preferably Analytics / Big Data/ Data Science / AI background.

Key Responsibilities : ( Data Developer Python, Spark)

Exp : 2 to 9 Yrs 

Development of data platforms, integration frameworks, processes, and code.

Develop and deliver APIs in Python or Scala for Business Intelligence applications build using a range of web languages

Develop comprehensive automated tests for features via end-to-end integration tests, performance tests, acceptance tests and unit tests.

Elaborate stories in a collaborative agile environment (SCRUM or Kanban)

Familiarity with cloud platforms like GCP, AWS or Azure.

Experience with large data volumes.

Familiarity with writing rest-based services.

Experience with distributed processing and systems

Experience with Hadoop / Spark toolsets

Experience with relational database management systems (RDBMS)

Experience with Data Flow development

Knowledge of Agile and associated development techniques including:

n 

• Proficiency in shell scripting
• Proficiency in automation of tasks
• Proficiency in Pyspark/Python
• Proficiency in writing and understanding of sqoop
• Understanding of CloudEra manager
• Good understanding of RDBMS
• Good understanding of Excel

What you’ll do

• Deliver plugins for our Python-based ETL pipelines.
• Deliver Python microservices for provisioning and managing cloud infrastructure.
• Implement algorithms to analyse large data sets.
• Draft design documents that translate requirements into code.
• Deal with challenges associated with handling large volumes of data.
• Assume responsibilities from technical design through technical client support.
• Manage expectations with internal stakeholders and context-switch in a fast paced environment.
• Thrive in an environment that uses AWS and Elasticsearch extensively.
• Keep abreast of technology and contribute to the engineering strategy.
• Champion best development practices and provide mentorship.

What we’re looking for

• Experience in Python 3.
• Python libraries used for data (such as pandas, numpy).
• AWS.
• Elasticsearch.
• Performance tuning.
• Object Oriented Design and Modelling.
• Delivering complex software, ideally in a FinTech setting.
• CI/CD tools.
• Knowledge of design patterns.
• Sharp analytical and problem-solving skills.
• Strong sense of ownership.
• Demonstrable desire to learn and grow.
• Excellent written and oral communication skills.
• Mature collaboration and mentoring abilities.

About SteelEye Culture

• Work from home until you are vaccinated against COVID-19
• Top of the line health insurance • Order discounted meals every day from a dedicated portal
• Fair and simple salary structure
• 30+ holidays in a year
• Fresh fruits every day
• Centrally located. 5 mins to the nearest metro station (MG Road)
• Measured on output and not input

We are a nascent quantitative hedge fund led by an MIT PhD and Math Olympiad medallist, offering opportunities to grow with us as we build out the team. Our fund has  world class investors and big data experts as part of the GP,  top-notch ML experts as advisers to the fund, plus has equity funding to grow the team, license data and scale the data processing.

We are interested in researching and taking in live a variety of quantitative strategies based on historic and live market data, alternative datasets, social media data (both audio and video) and stock fundamental data.

You would join, and, if qualified, lead a growing team of data scientists and researchers, and be responsible for a complete lifecycle of quantitative strategy implementation and trading.

Requirements:

• Atleast 3 years of relevant ML experience
• Graduation date : 2018 and earlier
•   3-5 years of experience in high level Python programming.
• Master Degree (or Phd) in quantitative disciplines such as Statistics, Mathematics, Physics, Computer Science in top universities.
•   Good knowledge of applied and theoretical statistics, linear algebra and machine learning techniques. 
•   Ability to leverage financial and statistical insights to research, explore and harness a large collection of quantitative strategies and financial datasets in order to build strong predictive models.
• Should take ownership for the research, design, development and implementation of the strategy development and effectively communicate with other team mates
•   Prior experience and good knowledge of lifecycle and pitfalls of algorithmic strategy development and modelling. 
•   Good practical knowledge in understanding financial statements, value investing, portfolio and risk management techniques.
•   A proven ability to lead and drive innovation to solve challenges and road blocks in project completion.
• A valid Github profile with some activity in it

Bonus to have:

•   Experience in storing and retrieving data from large and complex time series databases
•   Very good practical knowledge on time-series modelling and forecasting (ARIMA, ARCH and Stochastic modelling)
•   Prior experience in optimizing and back testing quantitative strategies, doing return and risk attribution, feature/factor evaluation. 
•   Knowledge of AWS/Cloud ecosystem is an added plus (EC2s, Lambda, EKS, Sagemaker etc.) 
•   Knowledge of REST APIs and data extracting and cleaning techniques 
•   Good to have experience in Pyspark or any other big data programming/parallel computing
•   Familiarity with derivatives, knowledge in multiple asset classes along with Equities.
•   Any progress towards CFA or FRM is a bonus
• Average tenure of atleast 1.5 years in a company