Data Analyst

Data Scientist – Program Embedded 

Job Description:   

We are seeking a highly skilled and motivated senior data scientist to support a big data program. The successful candidate will play a pivotal role in supporting multiple projects in this program covering traditional tasks from revenue management, demand forecasting, improving customer experience to testing/using new tools/platforms such as Copilot Fabric for different purpose. The expected candidate would have deep expertise in machine learning methodology and applications. And he/she should have completed multiple large scale data science projects (full cycle from ideation to BAU). Beyond technical expertise, problem solving in complex set-up will be key to the success for this role. This is a data science role directly embedded into the program/projects, stake holder management and collaborations with patterner are crucial to the success on this role (on top of the deep expertise). 

What we are looking for: 

1. Highly efficient in Python/Pyspark/R. 
2. Understand MLOps concepts, working experience in product industrialization (from Data Science point of view). Experience in building product for live deployment, and continuous development and continuous integration. 
3. Familiar with cloud platforms such as Azure, GCP, and the data management systems on such platform. Familiar with Databricks and product deployment on Databricks. 
4. Experience in ML projects involving techniques: Regression, Time Series, Clustering, Classification, Dimension Reduction, Anomaly detection with traditional ML approaches and DL approaches. 
5. Solid background in statistics, probability distributions, A/B testing validation, univariate/multivariate analysis, hypothesis test for different purpose, data augmentation etc. 
6. Familiar with designing testing framework for different modelling practice/projects based on business needs. 
7. Exposure to Gen AI tools and enthusiastic about experimenting and have new ideas on what can be done. 
8. If they have improved an internal company process using an AI tool, that would be great (e.g. process simplification, manual task automation, auto emails) 
9. Ideally, 10+ years of experience, and have been on independent business facing roles. 
10. CPG or retail as a data scientist would be nice, but not number one priority, especially for those who have navigated through multiple industries. 
11. Being proactive and collaborative would be essential. 

Some projects examples within the program: 

1. Test new tools/platforms such as Copilo, Fabric for commercial reporting. Testing, validation and build trust. 
2. Building algorithms for predicting trend in category, consumptions to support dashboards. 
3. Revenue Growth Management, create/understand the algorithms behind the tools (can be built by 3rd parties) we need to maintain or choose to improve. Able to prioritize and build product roadmap. Able to design new solutions and articulate/quantify the limitation of the solutions. 
4. Demand forecasting, create localized forecasts to improve in store availability. Proper model monitoring for early detection of potential issues in the forecast focusing particularly on improving the end user experience. 

• Develop, train, and optimize machine learning models using Python, ML algorithms, deep learning frameworks (e.g., TensorFlow, PyTorch), and other relevant technologies.
• Implement MLOps best practices, including model deployment, monitoring, and versioning.
• Utilize Vertex AI, MLFlow, KubeFlow, TFX, and other relevant MLOps tools and frameworks to streamline the machine learning lifecycle.
• Collaborate with cross-functional teams to design and implement CI/CD pipelines for continuous integration and deployment using tools such as GitHub Actions, TeamCity, and similar platforms.
• Conduct research and stay up-to-date with the latest advancements in machine learning, deep learning, and MLOps technologies.
• Provide guidance and support to data scientists and software engineers on best practices for machine learning development and deployment.
• Assist in developing tooling strategies by evaluating various options, vendors, and product roadmaps to enhance the efficiency and effectiveness of our AI and data science initiatives.

1. Data Engineer

 Required skill set: AWS GLUE, AWS LAMBDA, AWS SNS/SQS, AWS ATHENA, SPARK, SNOWFLAKE, PYTHON

Mandatory Requirements  

• Experience in AWS Glue
• Experience in Apache Parquet 
• Proficient in AWS S3 and data lake 
• Knowledge of Snowflake
• Understanding of file-based ingestion best practices.
• Scripting language - Python & pyspark 

CORE RESPONSIBILITIES 

• Create and manage cloud resources in AWS 
• Data ingestion from different data sources which exposes data using different technologies, such as: RDBMS, REST HTTP API, flat files, Streams, and Time series data based on various proprietary systems. Implement data ingestion and processing with the help of Big Data technologies 
• Data processing/transformation using various technologies such as Spark and Cloud Services. You will need to understand your part of business logic and implement it using the language supported by the base data platform 
• Develop automated data quality check to make sure right data enters the platform and verifying the results of the calculations 
• Develop an infrastructure to collect, transform, combine and publish/distribute customer data.
• Define process improvement opportunities to optimize data collection, insights and displays.
• Ensure data and results are accessible, scalable, efficient, accurate, complete and flexible 
• Identify and interpret trends and patterns from complex data sets 
• Construct a framework utilizing data visualization tools and techniques to present consolidated analytical and actionable results to relevant stakeholders. 
• Key participant in regular Scrum ceremonies with the agile teams  
• Proficient at developing queries, writing reports and presenting findings 
• Mentor junior members and bring best industry practices 

 QUALIFICATIONS 

• 5-7+ years’ experience as data engineer in consumer finance or equivalent industry (consumer loans, collections, servicing, optional product, and insurance sales) 
• Strong background in math, statistics, computer science, data science or related discipline
• Advanced knowledge one of language: Java, Scala, Python, C# 
• Production experience with: HDFS, YARN, Hive, Spark, Kafka, Oozie / Airflow, Amazon Web Services (AWS), Docker / Kubernetes, Snowflake  
• Proficient with
• Data mining/programming tools (e.g. SAS, SQL, R, Python)
• Database technologies (e.g. PostgreSQL, Redshift, Snowflake. and Greenplum)
• Data visualization (e.g. Tableau, Looker, MicroStrategy)
• Comfortable learning about and deploying new technologies and tools. 
• Organizational skills and the ability to handle multiple projects and priorities simultaneously and meet established deadlines. 
• Good written and oral communication skills and ability to present results to non-technical audiences 
• Knowledge of business intelligence and analytical tools, technologies and techniques.

Familiarity and experience in the following is a plus:  

• AWS certification
• Spark Streaming 
• Kafka Streaming / Kafka Connect 
• ELK Stack 
• Cassandra / MongoDB 
• CI/CD: Jenkins, GitLab, Jira, Confluence other related tools

Data Engineer JD:

• Designing, developing, constructing, installing, testing and maintaining the complete data management & processing systems.
• Building highly scalable, robust, fault-tolerant, & secure user data platform adhering to data protection laws.
• Taking care of the complete ETL (Extract, Transform & Load) process.
• Ensuring architecture is planned in such a way that it meets all the business requirements.
• Exploring new ways of using existing data, to provide more insights out of it.
• Proposing ways to improve data quality, reliability & efficiency of the whole system.
• Creating data models to reduce system complexity and hence increase efficiency & reduce cost.
• Introducing new data management tools & technologies into the existing system to make it more efficient.
• Setting up monitoring and alarming on data pipeline jobs to detect failures and anomalies

What do we expect from you?

• BS/MS in Computer Science or equivalent experience
• 5 years of recent experience in Big Data Engineering.
• Good experience in working with Hadoop and Big Data technologies like HDFS, Pig, Hive, Zookeeper, Storm, Spark, Airflow and NoSQL systems
• Excellent programming and debugging skills in Java or Python.
• Apache spark, python, hands on experience in deploying ML models
• Has worked on streaming and realtime pipelines
• Experience with Apache Kafka or has worked with any of Spark Streaming, Flume or Storm

Focus Area:

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. 

Job Description - Sr Azure Data Engineer

Roles & Responsibilities:

1. Hands-on programming in C# / .Net,
2. Develop serverless applications using Azure Function Apps.
3. Writing complex SQL Queries, Stored procedures, and Views. 
4. Creating Data processing pipeline(s).
5. Develop / Manage large-scale Data Warehousing and Data processing solutions.
6. Provide clean, usable data and recommend data efficiency, quality, and data integrity.

Skills

1. Should have working experience on C# /.Net.
2. Proficient with writing SQL queries, Stored Procedures, and Views
3. Should have worked on Azure Cloud Stack.
4. Should have working experience ofin developing serverless code.
5. Must have MANDATORILY worked on Azure Data Factory.

Experience 

1. 4+ years of relevant experience

•  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.