ETL Developer

at PriceSenz

JOB DESCRIPTION – SENIOR DATA SCIENTIST

Who We Are

At ThinkBumblebee, we are committed to understand growth that leads to businesses making better use of their data. Through our dedication to using the latest tech stack, engineering methods and many more, we are committed to help companies put their customers at the centre of the business.

We're looking for a motivated, analytically-minded candidate who wants to be part of a start-up style environment. Ideally you have a broad skill set and is willing to take on (or teach yourself to take on) any challenge.

PURPOSE OF ROLE

• Understand and solve complex business problems with sound analytical prowess and help business with impactful insights in decision-making
• To make sure any roadblocks in implementation is brought to the notice of relevant stakeholders so that project timelines do not get affected
• Document every aspect of the project in standard way, for future purposes
• Articulate technical complexities to the senior leadership in a simple and easy manner.

KEY TASKS AND ACCOUNTABILITIES

• Understand the business problem and translate that to a data-driven analytical/statistical problem; Own the solution building process
• Create appropriate datasets and develop statistical data models
• Translate complex statistical analysis over large datasets into insights and actions
• Analyse results and present to stakeholders
• Communicate the insights using business-friendly presentations
• Help and mentor other Associate Data Scientists
• Build a pipeline of the project which is production-ready
• Build dashboards for easy consumption of solutions

BUSINESS ENVIRONMENT

• Work with stakeholders to understand their business problems, translate those problems into data-driven analytical solutions which can best address those business problems
• Use data science/analytics prowess to provide answers to key business questions. Could be in any domain (e.g. Retail, Media, OTT)
• Summarize insights and recommendations to be presented back to the business
• Use innovative methods to continuously improve the quality of statistical models

SUCCESS CRITERIA

• Building an efficient model that helps the business stakeholder to measure outcomes of their decisions
• High quality & production-ready codes written within timelines given
• Following processes and adhering to documentation goals
• High quality presentations
• Questions from business stakeholders answered satisfactorily within agreeable time

EXPERIENCE

• Minimum 3 years in data science role with experience of building end-to-end solution as well as implementing or operationalizing the same solution
• Must have done EDA extensively for a minimum of 3 years
• Expertise strongly desired in building statistical and machine learning algorithms for:
  • Regression
  • Time series
  • Ensemble learning
  • Bayesian stats
  • Classification
  • Clustering
  • NLP
  • Anomaly Detection
• Hands-on experience in Bayesian Stats would be preferred
• Exposure to optimization and simulation techniques (good to have)

SKILLS

• Proven skills in translating statistics into insights. Sound knowledge in statistical inference and hypothesis testing
• English (Fluent)
• Microsoft Office (mandatory)
• Expert in Python (mandatory)
• Advanced Excel (mandatory)
• SQL (at least one database)
• Reporting Tool (Any Tool – Must be open to learning tools based on the requirement)

EDUCATION

• B Tech (or equivalent) in any branch or degree in Statistics, Applied Statistics, Economics, Econometrics, Operations Research or any other quantitative fields

Mandatory Requirements

• Strong written and verbal English skills
• Strong analytical, logic and quantitative ability
• Desire to solve business problems in any domain through analytical/data-driven solution
• Ability to generate business insights from statistical model outputs
• Microsoft Office skills (Excel, PowerPoint, Word)
• Python

At ThinkBumbleBee Analytics, we derive insights that allow our clients make a
scientific decisions. We believe in demanding more from the fields of
Mathematics, Computer Science and Business Logic. Combine these and we
show our clients a 360-degree view of their business.

The Person

• Articulate
• High Energy
• Passion to learn
• High sense of ownership
• Ability to work in a fast-paced and deadline driven environment
• Loves technology
• Highly skilled at Data Interpretation
• Problem solver
• Ability to narrate story to the business stakeholders
• Generate insights and the ability to turn them into actions and decisions

Skills to work in a challenging, complex project environment

• Need you to be naturally curious and have a passion for understanding consumer behavior
• A high level of motivation, passion and high sense of ownership
• Excellent communication skills needed to manage an incredibly diverse slate of work, clients, and team personalities
• Flexibility to work on multiple projects and deadline-driven fast-paced environment
• Ability to work in ambiguity and manage chaos

Technical Skills

1. Solid understanding and experience in statistical methods and programming
2. Experience in both supervised (Random Forest, AB Tests, Linear Regression,  Classification) and unsupervised learning (clustering, PCA, LDA)
3. Experience in any Cloud Platform (AWS/GCP/Azure)
4. High level of proficiency in the following: 

1. Adapt SQL to query other relational databases
2. Understanding ER Diagram
3. Write Production Level Code (Unit Testing, Modularity, etc)
4. Write efficient SQL queries

1. Build Python (Pandas) code using variables, relational operators, logical operators, loops, and functions 
2. OOPS 
3. Multi Processing Libraries
4. DASK
5. Visualisation - Seaborn, Matplot lIb

C. Implementation of statistics using Python:

1. Descriptive statistics using Python code -  calculating mean,median, mode, standard deviation, and percentiles; and identifying outliers
2. Use Python code to test hypothesis, calculate correlations and to predict a continuous variable using regression
3. Sampling Procedures
4. Inferential Statistics
5. Parametric and Non Parametric Tests
6. Non Linear Regression
7. Validate regression assumptions

Qualifications:-

• BE/BTech in Computer Science/Statistics
• Should have a minimum 3 years’ experience in Data Science 

• 4-10 years of experience in software development.
• At least 2 years of relevant work experience on large scale Data applications.
• Strong coding experience in Java is mandatory
• Good aptitude, strong problem solving abilities, and analytical skills, ability to take ownership as appropriate
• Should be able to do coding, debugging, performance tuning and deploying the apps to Prod.
• Should have good working experience on
• o Hadoop ecosystem (HDFS, Hive, Yarn, File formats like Avro/Parquet)
• o Kafka
• o J2EE Frameworks (Spring/Hibernate/REST)
• o Spark Streaming or any other streaming technology.
• Strong coding experience in Java is mandatory
• Ability to work on the sprint stories to completion along with Unit test case coverage.
• Experience working in Agile Methodology
• Excellent communication and coordination skills
• Knowledgeable (and preferred hands on) - UNIX environments, different continuous integration tools.
• Must be able to integrate quickly into the team and work independently towards team goals

• Take the complete responsibility of the sprint stories' execution
• Be accountable for the delivery of the tasks in the defined timelines with good quality.
• Follow the processes for project execution and delivery.
• Follow agile methodology
• Work with the team lead closely and contribute to the smooth delivery of the project.
• Understand/define the architecture and discuss the pros-cons of the same with the team
• Involve in the brainstorming sessions and suggest improvements in the architecture/design.
• Work with other team leads to get the architecture/design reviewed.
• Work with the clients and counter-parts (in US) of the project.
• Keep all the stakeholders updated about the project/task status/risks/issues if there are any.

• Be the analytical expert in Kaleidofin, managing ambiguous problems by using data to execute sophisticated quantitative modeling and deliver actionable insights.
• Develop comprehensive skills including project management, business judgment, analytical problem solving and technical depth.
• Become an expert on data and trends, both internal and external to Kaleidofin.
• Communicate key state of the business metrics and develop dashboards to enable teams to understand business metrics independently.
• Collaborate with stakeholders across teams to drive data analysis for key business questions, communicate insights and drive the planning process with company executives.
• Automate scheduling and distribution of reports and support auditing and value realization.
• Partner with enterprise architects to define and ensure proposed.
• Business Intelligence solutions adhere to an enterprise reference architecture.
• Design robust data-centric solutions and architecture that incorporates technology and strong BI solutions to scale up and eliminate repetitive tasks.

• Experience leading development efforts through all phases of SDLC.
• 2+ years "hands-on" experience designing Analytics and Business Intelligence solutions.
• Experience with Quicksight, PowerBI, Tableau and Qlik is a plus.
• Hands on experience in SQL, data management, and scripting (preferably Python).
• Strong data visualisation design skills, data modeling and inference skills.
• Hands-on and experience in managing small teams.
• Financial services experience preferred, but not mandatory.
• Strong knowledge of architectural principles, tools, frameworks, and best practices.
• Excellent communication and presentation skills to communicate and collaborate with all levels of the organisation.
• Preferred candidates with less than 30 days notice period.

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

• Create and maintain optimal data pipeline architecture,
• Assemble large, complex data sets that meet functional / non-functional business requirements.
• Author data services using a variety of programming languages
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and Azure ‘big data’ technologies.
• Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics.
• Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
• Keep our data separated and secure across national boundaries through multiple data centres and Azure regions.
• Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
• Work with data and analytics experts to strive for greater functionality in our data systems.
• Work in an Agile environment with Scrum teams.
• Ensure data quality and help in achieving data governance.

• 2+ years of experience in a Data Engineer role
• Undergraduate degree required (Graduate degree preferred) in Computer Science, Statistics, Informatics, Information Systems or another quantitative field.
• Experience using the following software/tools:
• Experience with big data tools: Hadoop, Spark, Kafka, etc.
• Experience with relational SQL and NoSQL databases
• Experience with data pipeline and workflow management tools
• Experience with Azure cloud services: ADLS, ADF, ADLA, AAS
• Experience with stream-processing systems: Storm, Spark-Streaming, etc.
• Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.
• Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases
• Understanding of ELT and ETL patterns and when to use each. Understanding of data models and transforming data into the models
• Experience building and optimizing ‘big data’ data pipelines, architectures, and data sets
• Strong analytic skills related to working with unstructured datasets
• Build processes supporting data transformation, data structures, metadata, dependency, and workload management
• Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores
• Experience supporting and working with cross-functional teams in a dynamic environment

•  We are looking for a Data Engineer with 3-5 years experience in Python, SQL, AWS (EC2, S3, Elastic Beanstalk, API Gateway), and Java.
• The applicant must be able to perform Data Mapping (data type conversion, schema harmonization) using Python, SQL, and Java.
• The applicant must be familiar with and have programmed ETL interfaces (OAUTH, REST API, ODBC) using the same languages.
• The company is looking for someone who shows an eagerness to learn and who asks concise questions when communicating with teammates.