Associate Director - Analytics

Job Title:
Data Analyst

Job Brief:
The successful candidate will turn data into information, information into insight and insight into business decisions.

Data Analyst Job Duties
Data analyst responsibilities include conducting full lifecycle analysis to include requirements, activities and design. Data analysts will develop analysis and reporting capabilities. They will also monitor performance
and quality control plans to identify improvements.

About Us
We began in 2015 with an entrepreneurial vision to bring a digital change in the manufacturing landscape of India. With a team of 300+ we are working towards the digital transformation of business in the manufacturing industry across domains like Footwear, Apparel, Textile, Accessories etc. We are backed by investors such as
Info Edge (Naukri.com), Matrix Partners, Sequoia, Water Bridge Ventures and select Industry leaders.
Today, we have enabled 2000+ Manufacturers to digitize their distribution channel.

Responsibilities
● Interpret data, analyze results using statistical techniques and provide ongoing reports.
● Develop and implement databases, data collection systems, data analytics and other strategies that
optimize statistical efficiency and quality.
● Acquire data from primary or secondary data sources and maintain databases/data systems.
● Identify, analyze, and interpret trends or patterns in complex data sets.
● Filter and “clean” data by reviewing computer reports, printouts, and performance indicators to locate and
correct code problems.
● Work with management to prioritize business and information needs.
● Locate and define new process improvement opportunities.
Requirements
● Proven working experience as a Data Analyst or Business Data Analyst.
● Technical expertise regarding data models, database design development, data mining and segmentation
techniques.
● Strong knowledge of and experience with reporting packages (Business Objects etc), databases (SQL etc),
programming (XML, Javascript, or ETL frameworks).
● Knowledge of statistics and experience using statistical packages for analyzing datasets (Excel, SPSS, SAS
etc).
● Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of
information with attention to detail and accuracy.
● Adept at queries, report writing and presenting findings.


Job Location
South Delhi, New Delhi

Someone who has prior experience in Product Analytics/Marketing Analytics/Growth Analytics/Consumer analytics domain.

Has the ability to define success metrics for different initiatives or campaigns, drive ROI analysis & provide recommendations.

Strong analytics acumen and problem solving skills.

Good understanding of Clickstream/App events data, ability to build and understand user journeys across platforms.

Understanding of LTV modelling

Strong SQL skills and comfortable with python programming.

Basic knowledge of different regression models & clustering techniques.

4+ year experience in advanced analytics, model building, statistical modeling,
• Solid technical / data-mining skills and ability to work with large volumes of data; extract
and manipulate large datasets using common tools such as Python and SQL other
programming/scripting languages to translate data into business decisions/results
• Be data-driven and outcome-focused
• Must have good business judgment with demonstrated ability to think creatively and
strategically
• Must be an intuitive, organized analytical thinker, with the ability to perform detailed
analysis
• Takes personal ownership; Self-starter; Ability to drive projects with minimal guidance
and focus on high impact work
• Learns continuously; Seeks out knowledge, ideas and feedback.
• Looks for opportunities to build owns skills, knowledge and expertise.
• Experience with big data and cloud computing viz. Spark, Hadoop (MapReduce, PIG,
HIVE)
• Experience in risk and credit score domains preferred
• Comfortable with ambiguity and frequent context-switching in a fast-paced
environment

Company Profile
XressBees – a logistics company started in 2015 – is amongst the fastest growing companies of its sector. Our
vision to evolve into a strong full-service logistics organization reflects itself in the various lines of business like B2C
logistics 3PL, B2B Xpress, Hyperlocal and Cross border Logistics.
Our strong domain expertise and constant focus on innovation has helped us rapidly evolve as the most trusted
logistics partner of India. XB has progressively carved our way towards best-in-class technology platforms, an
extensive logistics network reach, and a seamless last mile management system.
While on this aggressive growth path, we seek to become the one-stop-shop for end-to-end logistics solutions. Our
big focus areas for the very near future include strengthening our presence as service providers of choice and
leveraging the power of technology to drive supply chain efficiencies.
Job Overview
XpressBees would enrich and scale its end-to-end logistics solutions at a high pace. This is a great opportunity to join
the team working on forming and delivering the operational strategy behind Artificial Intelligence / Machine Learning
and Data Engineering, leading projects and teams of AI Engineers collaborating with Data Scientists. In your role, you
will build high performance AI/ML solutions using groundbreaking AI/ML and BigData technologies. You will need to
understand business requirements and convert them to a solvable data science problem statement. You will be
involved in end to end AI/ML projects, starting from smaller scale POCs all the way to full scale ML pipelines in
production.
Seasoned AI/ML Engineers would own the implementation and productionzation of cutting-edge AI driven algorithmic
components for search, recommendation and insights to improve the efficiencies of the logistics supply chain and
serve the customer better.
You will apply innovative ML tools and concepts to deliver value to our teams and customers and make an impact to
the organization while solving challenging problems in the areas of AI, ML , Data Analytics and Computer Science.
Opportunities for application:
- Route Optimization
- Address / Geo-Coding Engine
- Anomaly detection, Computer Vision (e.g. loading / unloading)
- Fraud Detection (fake delivery attempts)
- Promise Recommendation Engine etc.
- Customer & Tech support solutions, e.g. chat bots.
- Breach detection / prediction
An Artificial Intelligence Engineer would apply himself/herself in the areas of -
- Deep Learning, NLP, Reinforcement Learning
- Machine Learning - Logistic Regression, Decision Trees, Random Forests, XGBoost, etc..
- Driving Optimization via LPs, MILPs, Stochastic Programs, and MDPs
- Operations Research, Supply Chain Optimization, and Data Analytics/Visualization
- Computer Vision and OCR technologies
The AI Engineering team enables internal teams to add AI capabilities to their Apps and Workflows easily via APIs
without needing to build AI expertise in each team – Decision Support, NLP, Computer Vision, for Public Clouds and
Enterprise in NLU, Vision and Conversational AI.Candidate is adept at working with large data sets to find
opportunities for product and process optimization and using models to test the effectiveness of different courses of
action. They must have knowledge using a variety of data mining/data analysis methods, using a variety of data tools,
building, and implementing models, using/creating algorithms, and creating/running simulations. They must be
comfortable working with a wide range of stakeholders and functional teams. The right candidate will have a passion
for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes.

Roles & Responsibilities
● Develop scalable infrastructure, including microservices and backend, that automates training and
deployment of ML models.
● Building cloud services in Decision Support (Anomaly Detection, Time series forecasting, Fraud detection,
Risk prevention, Predictive analytics), computer vision, natural language processing (NLP) and speech that
work out of the box.
● Brainstorm and Design various POCs using ML/DL/NLP solutions for new or existing enterprise problems.
● Work with fellow data scientists/SW engineers to build out other parts of the infrastructure, effectively
communicating your needs and understanding theirs and address external and internal shareholder's
product challenges.
● Build core of Artificial Intelligence and AI Services such as Decision Support, Vision, Speech, Text, NLP, NLU,
and others.
● Leverage Cloud technology –AWS, GCP, Azure
● Experiment with ML models in Python using machine learning libraries (Pytorch, Tensorflow), Big Data,
Hadoop, HBase, Spark, etc
● Work with stakeholders throughout the organization to identify opportunities for leveraging company data to
drive business solutions.
● Mine and analyze data from company databases to drive optimization and improvement of product
development, marketing techniques and business strategies.
● Assess the effectiveness and accuracy of new data sources and data gathering techniques.
● Develop custom data models and algorithms to apply to data sets.
● Use predictive modeling to increase and optimize customer experiences, supply chain metric and other
business outcomes.
● Develop company A/B testing framework and test model quality.
● Coordinate with different functional teams to implement models and monitor outcomes.
● Develop processes and tools to monitor and analyze model performance and data accuracy.
● Develop scalable infrastructure, including microservices and backend, that automates training and
deployment of ML models.
● Brainstorm and Design various POCs using ML/DL/NLP solutions for new or existing enterprise problems.
● Work with fellow data scientists/SW engineers to build out other parts of the infrastructure, effectively
communicating your needs and understanding theirs and address external and internal shareholder's
product challenges.
● Deliver machine learning and data science projects with data science techniques and associated libraries
such as AI/ ML or equivalent NLP (Natural Language Processing) packages. Such techniques include a good
to phenomenal understanding of statistical models, probabilistic algorithms, classification, clustering, deep
learning or related approaches as it applies to financial applications.
● The role will encourage you to learn a wide array of capabilities, toolsets and architectural patterns for
successful delivery.
What is required of you?
You will get an opportunity to build and operate a suite of massive scale, integrated data/ML platforms in a broadly
distributed, multi-tenant cloud environment.
● B.S., M.S., or Ph.D. in Computer Science, Computer Engineering
● Coding knowledge and experience with several languages: C, C++, Java,JavaScript, etc.
● Experience with building high-performance, resilient, scalable, and well-engineered systems
● Experience in CI/CD and development best practices, instrumentation, logging systems
● Experience using statistical computer languages (R, Python, SLQ, etc.) to manipulate data and draw insights
from large data sets.
● Experience working with and creating data architectures.
● Good understanding of various machine learning and natural language processing technologies, such as
classification, information retrieval, clustering, knowledge graph, semi-supervised learning and ranking.

● Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest,
Boosting, Trees, text mining, social network analysis, etc.
● Knowledge on using web services: Redshift, S3, Spark, Digital Ocean, etc.
● Knowledge on creating and using advanced machine learning algorithms and statistics: regression,
simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc.
● Knowledge on analyzing data from 3rd party providers: Google Analytics, Site Catalyst, Core metrics,
AdWords, Crimson Hexagon, Facebook Insights, etc.
● Knowledge on distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, MySQL, Kafka etc.
● Knowledge on visualizing/presenting data for stakeholders using: Quicksight, Periscope, Business Objects,
D3, ggplot, Tableau etc.
● Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural
networks, etc.) and their real-world advantages/drawbacks.
● Knowledge of advanced statistical techniques and concepts (regression, properties of distributions,
statistical tests, and proper usage, etc.) and experience with applications.
● Experience building data pipelines that prep data for Machine learning and complete feedback loops.
● Knowledge of Machine Learning lifecycle and experience working with data scientists
● Experience with Relational databases and NoSQL databases
● Experience with workflow scheduling / orchestration such as Airflow or Oozie
● Working knowledge of current techniques and approaches in machine learning and statistical or
mathematical models
● Strong Data Engineering & ETL skills to build scalable data pipelines. Exposure to data streaming stack (e.g.
Kafka)
● Relevant experience in fine tuning and optimizing ML (especially Deep Learning) models to bring down
serving latency.
● Exposure to ML model productionzation stack (e.g. MLFlow, Docker)
● Excellent exploratory data analysis skills to slice & dice data at scale using SQL in Redshift/BigQuery.

Location: Bangalore
Work Timing: 5 Days A Week

Responsibilities include:
• Ensure right stakeholders gets right information at right time
• Requirement gathering with stakeholders to understand their data requirement
• Creating and deploying reports
• Participate actively in datamarts design discussions
• Work on both RDBMS as well as Big Data for designing BI Solutions
• Write code (queries/procedures) in SQL / Hive / Drill that is both functional and elegant,
following appropriate design patterns
• Design and plan BI solutions to automate regular reporting
• Debugging, monitoring and troubleshooting BI solutions
• Creating and deploying datamarts
• Writing relational and multidimensional database queries
• Integrate heterogeneous data sources into BI solutions
• Ensure Data Integrity of data flowing from heterogeneous data sources into BI solutions.

Minimum Job Qualifications:
• BE/B.Tech in Computer Science/IT from Top Colleges
• 1-5 years of experience in Datawarehousing and SQL
• Excellent Analytical Knowledge
• Excellent technical as well as communication skills
• Attention to even the smallest detail is mandatory
• Knowledge of SQL query writing and performance tuning
• Knowledge of Big Data technologies like Apache Hadoop, Apache Hive, Apache Drill
• Knowledge of fundamentals of Business Intelligence
• In-depth knowledge of RDBMS systems, Datawarehousing and Datamarts
• Smart, motivated and team oriented
Desirable Requirements
• Sound knowledge of software development in Programming (preferably Java )
• Knowledge of the software development lifecycle (SDLC) and models

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. 

• 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.

• Responsible for developing and maintaining applications with PySpark