Data Scientist

Job Description: Data Engineer

We are looking for a curious Data Engineer to join our extremely fast-growing Tech Team at StanPlus

About RED.Health (Formerly Stanplus Technologies)

Get to know the team:

Join our team and help us build the world’s fastest and most reliable emergency response system using cutting-edge technology.

Because every second counts in an emergency, we are building systems and flows with 4 9s of reliability to ensure that our technology is always there when people need it the most. We are looking for distributed systems experts who can help us perfect the architecture behind our key design principles: scalability, reliability, programmability, and resiliency. Our system features a powerful dispatch engine that connects emergency service providers with patients in real-time

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Key Responsibilities

●     Build Data ETL Pipelines

●     Develop data set processes

●     Strong analytic skills related to working with unstructured datasets

●     Evaluate business needs and objectives

●     Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery

●     Interpret trends and patterns

●     Work with data and analytics experts to strive for greater functionality in our data system

●     Build algorithms and prototypes

●     Explore ways to enhance data quality and reliability

●     Work with the Executive, Product, Data, and D   esign teams, to assist with data-related technical issues and support their data infrastructure needs.

●     Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics.

Key Requirements

●     Proven experience as a data engineer, software developer, or similar of at least 3 years.

●     Bachelor's / Master’s degree in data engineering, big data analytics, computer engineering, or related field.

●     Experience with big data tools: Hadoop, Spark, Kafka, etc.

●     Experience with relational SQL and NoSQL databases, including Postgres and Cassandra.

●     Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.

●     Experience with Azure, AWS cloud services: EC2, EMR, RDS, Redshift

●     Experience with BigQuery

●     Experience with stream-processing systems: Storm, Spark-Streaming, etc.

●     Experience with languages: Python, Java, C++, Scala, SQL, R, etc.

●     Good hands-on with Hive, Presto.

Responsibilities

1. Create data funnels to feed into models via web, structured and unstructured data
2. Maintain coding standards using  SDLC, Git, AWS deployments etc
3. Keep abreast of developments in the field
4. Deploy models in production and monitor them
5. Documentations of processes and logic
6. Take ownership of the solution from code to deployment and performance

About Us: 

Small businesses are the backbone of the US economy, comprising almost half of the GDP and the private workforce. Yet, big banks don’t provide the access, assistance and modern tools that owners need to successfully grow their business. 

We started Novo to challenge the status quo—we’re on a mission to increase the GDP of the modern entrepreneur by creating the go-to banking platform for small businesses (SMBs). Novo is flipping the script of the banking world, and we’re excited to lead the small business banking revolution.

At Novo, we’re here to help entrepreneurs, freelancers, startups and SMBs achieve their financial goals by empowering them with an operating system that makes business banking as easy as iOS. We developed modern bank accounts and tools to help to save time and increase cash flow. Our unique product integrations enable easy access to tracking payments, transferring money internationally, managing business transactions and more. We’ve made a big impact in a short amount of time, helping thousands of organizations access powerfully simple business banking.  

We are looking for a Senior Data Scientist who is enthusiastic about using data and technology to solve complex business problems. If you're passionate about leading and helping to architect and develop thoughtful data solutions, then we want to chat. Are you ready to revolutionize the small business banking industry with us?

About the Role: (specific to the role-- describe the role activities/duties, who they interact with, what they are accountable for, how the role operates in the team, department and organization)

• Build and manage predictive models focussed on credit risk, fraud, conversions, churn, consumer behaviour etc
• Provides best practices, direction for data analytics and business decision making across multiple projects and functional areas
• Implements performance optimizations and best practices for scalable data models, pipelines and modelling
• Resolve blockers and help the team stay productive
• Take part in building the team and iterating on hiring processes

Requirements for the Role: (these are specific to the role-- technical skills and requirements to fulfill the job duties, certifications, years of experience, degree)

• 4+ years of experience in data science roles focussed on managing data processes, modelling and dashboarding
• Strong experience in python, SQL and in-depth understanding of modelling techniques
• Experience working with Pandas, scikit learn, visualization libraries like plotly, bokeh etc.
• Prior experience with credit risk modelling will be preferred
• Deep Knowledge of Python to write scripts to manipulate data and generate automated  reports

How We Define Success: (these are specific to the role-- should be tied to performance management, OKRs or general goals)

• Expand access to data driven decision making across the organization
• Solve problems in risk, marketing, growth, customer behaviour through analytics models that increase efficacy

Nice To Have, but Not Required:

• Experience in dashboarding libraries like Python Dash and exposure to CI/CD 
• Exposure to big data tools like Spark, and some core tech knowledge around API’s, data streaming etc.

Novo values diversity as a core tenant of the work we do and the businesses we serve. We are an equal opportunity employer, indiscriminate of race, religion, ethnicity, national origin, citizenship, gender, gender identity, sexual orientation, age, veteran status, disability, genetic information or any other protected characteristic. 

Required Skills:

• Proven work experience as an Enterprise / Data / Analytics Architect - Data Platform in HANA XSA, XS, Data Intelligence and SDI
• Can work on new and existing architecture decision in HANA XSA, XS, Data Intelligence and SDI
• Well versed with data architecture principles, software / web application design, API design, UI / UX capabilities, XSA / Cloud foundry architecture
• In-depth understand of database structure (HANA in-memory) principles.
• In-depth understand of ETL solutions and data integration strategy.
• Excellent knowledge of Software and Application design, API, XSA, and microservices concepts

Roles & Responsibilities:

• Advise and ensure compliance of the defined Data Architecture principle.
• Identifies new technologies update and development tools including new release/upgrade/patch as required. 
• Analyzes technical risks and advises on risk mitigation strategy.
• Advise and ensures compliance to existing and development required data and reporting standard including naming convention.

The time window is ideally AEST (8 am till 5 pm) which means starting at 3:30 am IST. We understand it can be very early for an SME supporting from India. Hence, we can consider the candidates who can support from at least 7 am IST (earlier is possible).

What are we looking for:

1. Strong experience in MySQL and writing advanced queries
2. Strong experience in Bash and Python
3. Familiarity with ElasticSearch, Redis, Java, NodeJS, ClickHouse, S3
4. Exposure to cloud services such as AWS, Azure, or GCP
5. 2+ years of experience in the production support
6. Strong experience in log management and performance monitoring like ELK, Prometheus + Grafana, logging services on various cloud platforms
7. Strong understanding of Linux OSes like Ubuntu, CentOS / Redhat Linux
8. Interest in learning new languages / framework as needed
9. Good written and oral communications skills
10. A growth mindset and passionate about building things from the ground up, and most importantly, you should be fun to work with

As a product solutions engineer, you will:

1. Analyze recorded runtime issues, diagnose and do occasional code fixes of low to medium complexity
2. Work with developers to find and correct more complex issues
3. Address urgent issues quickly, work within and measure against customer SLAs
4. Using shell and python scripts, and use scripting to actively automate manual / repetitive activities
5. Build anomaly detectors wherever applicable
6. Pass articulated feedback from customers to the development and product team
7. Maintain ongoing record of the operation of problem analysis and resolution in a on call monitoring system
8. Offer technical support needed in development

1. Data Steward :

Data Steward will collaborate and work closely within the group software engineering and business division. Data Steward has overall accountability for the group's / Divisions overall data and reporting posture by responsibly managing data assets, data lineage, and data access, supporting sound data analysis. This role requires focus on data strategy, execution, and support for projects, programs, application enhancements, and production data fixes. Makes well-thought-out decisions on complex or ambiguous data issues and establishes the data stewardship and information management strategy and direction for the group. Effectively communicates to individuals at various levels of the technical and business communities. This individual will become part of the corporate Data Quality and Data management/entity resolution team supporting various systems across the board.

Primary Responsibilities:

• Responsible for data quality and data accuracy across all group/division delivery initiatives.
• Responsible for data analysis, data profiling, data modeling, and data mapping capabilities.
• Responsible for reviewing and governing data queries and DML.
• Accountable for the assessment, delivery, quality, accuracy, and tracking of any production data fixes.
• Accountable for the performance, quality, and alignment to requirements for all data query design and development.
• Responsible for defining standards and best practices for data analysis, modeling, and queries.
• Responsible for understanding end-to-end data flows and identifying data dependencies in support of delivery, release, and change management.
• Responsible for the development and maintenance of an enterprise data dictionary that is aligned to data assets and the business glossary for the group responsible for the definition and maintenance of the group's data landscape including overlays with the technology landscape, end-to-end data flow/transformations, and data lineage.
• Responsible for rationalizing the group's reporting posture through the definition and maintenance of a reporting strategy and roadmap.
• Partners with the data governance team to ensure data solutions adhere to the organization’s data principles and guidelines.
• Owns group's data assets including reports, data warehouse, etc.
• Understand customer business use cases and be able to translate them to technical specifications and vision on how to implement a solution.
• Accountable for defining the performance tuning needs for all group data assets and managing the implementation of those requirements within the context of group initiatives as well as steady-state production.
• Partners with others in test data management and masking strategies and the creation of a reusable test data repository.
• Responsible for solving data-related issues and communicating resolutions with other solution domains.
• Actively and consistently support all efforts to simplify and enhance the Clinical Trial Predication use cases.
• Apply knowledge in analytic and statistical algorithms to help customers explore methods to improve their business.
• Contribute toward analytical research projects through all stages including concept formulation, determination of appropriate statistical methodology, data manipulation, research evaluation, and final research report.
• Visualize and report data findings creatively in a variety of visual formats that appropriately provide insight to the stakeholders.
• Achieve defined project goals within customer deadlines; proactively communicate status and escalate issues as needed.

Additional Responsibilities:

• Strong understanding of the Software Development Life Cycle (SDLC) with Agile Methodologies
• Knowledge and understanding of industry-standard/best practices requirements gathering methodologies.
• Knowledge and understanding of Information Technology systems and software development.
• Experience with data modeling and test data management tools.
• Experience in the data integration project • Good problem solving & decision-making skills.
• Good communication skills within the team, site, and with the customer

Knowledge, Skills and Abilities

• Technical expertise in data architecture principles and design aspects of various DBMS and reporting concepts.
• Solid understanding of key DBMS platforms like SQL Server, Azure SQL
• Results-oriented, diligent, and works with a sense of urgency. Assertive, responsible for his/her own work (self-directed), have a strong affinity for defining work in deliverables, and be willing to commit to deadlines.
• Experience in MDM tools like MS DQ, SAS DM Studio, Tamr, Profisee, Reltio etc.
• Experience in Report and Dashboard development
• Statistical and Machine Learning models
• Python (sklearn, numpy, pandas, genism)
• Nice to Have:
• 1yr of ETL experience
• Natural Language Processing
• Neural networks and Deep learning
• xperience in keras,tensorflow,spacy, nltk, LightGBM python library

Interaction :  Frequently interacts with subordinate supervisors.

Education : Bachelor’s degree, preferably in Computer Science, B.E or other quantitative field related to the area of assignment. Professional certification related to the area of assignment may be required

Experience :  7 years of Pharmaceutical /Biotech/life sciences experience, 5 years of Clinical Trials experience and knowledge, Excellent Documentation, Communication, and Presentation Skills including PowerPoint