Data Scientist

Analytics Job Description

We are hiring an Analytics Engineer to help drive our Business Intelligence efforts. You will

partner closely with leaders across the organization, working together to understand the how

and why of people, team and company challenges, workflows and culture. The team is

responsible for delivering data and insights that drive decision-making, execution, and

investments for our product initiatives.

You will work cross-functionally with product, marketing, sales, engineering, finance, and our

customer-facing teams enabling them with data and narratives about the customer journey.

You’ll also work closely with other data teams, such as data engineering and product analytics,

to ensure we are creating a strong data culture at Blend that enables our cross-functional partners

to be more data-informed.

Role : DataEngineer 

Please find below the JD for the DataEngineer Role..

  Location: Guindy,Chennai

How you’ll contribute:

• Develop objectives and metrics, ensure priorities are data-driven, and balance short-

term and long-term goals

• Develop deep analytical insights to inform and influence product roadmaps and

business decisions and help improve the consumer experience

• Work closely with GTM and supporting operations teams to author and develop core

data sets that empower analyses

• Deeply understand the business and proactively spot risks and opportunities

• Develop dashboards and define metrics that drive key business decisions

• Build and maintain scalable ETL pipelines via solutions such as Fivetran, Hightouch,

and Workato

• Design our Analytics and Business Intelligence architecture, assessing and

implementing new technologies that fitting

• Work with our engineering teams to continually make our data pipelines and tooling

more resilient

Who you are:

• Bachelor’s degree or equivalent required from an accredited institution with a

quantitative focus such as Economics, Operations Research, Statistics, Computer Science OR 1-3 Years of Experience as a Data Analyst, Data Engineer, Data Scientist

• Must have strong SQL and data modeling skills, with experience applying skills to

thoughtfully create data models in a warehouse environment.

• A proven track record of using analysis to drive key decisions and influence change

• Strong storyteller and ability to communicate effectively with managers and

executives

• Demonstrated ability to define metrics for product areas, understand the right

questions to ask and push back on stakeholders in the face of ambiguous, complex

problems, and work with diverse teams with different goals

• A passion for documentation.

• A solution-oriented growth mindset. You’ll need to be a self-starter and thrive in a

dynamic environment.

• A bias towards communication and collaboration with business and technical

stakeholders.

• Quantitative rigor and systems thinking.

• Prior startup experience is preferred, but not required.

• Interest or experience in machine learning techniques (such as clustering, decision

tree, and segmentation)

• Familiarity with a scientific computing language, such as Python, for data wrangling

and statistical analysis

• Experience with a SQL focused data transformation framework such as dbt

• Experience with a Business Intelligence Tool such as Mode/Tableau

Mandatory Skillset:

-Very Strong in SQL

-Spark OR pyspark OR Python

-Shell Scripting

Graas uses predictive AI to turbo-charge growth for eCommerce businesses. We are “Growth-as-a-Service”. Graas is a technology solution provider using predictive AI to turbo-charge growth for eCommerce businesses. Graas integrates traditional data silos and applies a machine-learning AI engine, acting as an in-house data scientist to predict trends and give real-time insights and actionable recommendations for brands. The platform can also turn insights into action by seamlessly executing these recommendations across marketplace store fronts, brand.coms, social and conversational commerce, performance marketing, inventory management, warehousing, and last mile logistics - all of which impacts a brand’s bottom line, driving profitable growth.

Location – Pune

Job Responsibilities

• Work closely with data scientists and data analysts to build models and continuous data monitoring workflows.
• Implement algorithms / models within companies recommendation engine framework.
• Own the MLOps life-cycle; build and own ML model life-cycle management process encompassing coding to building robust model monitoring workflows.
• Consult with product and business teams to build prototypes and then deploy holistic machine learning solutions.
• Recommend and implement architecture to deploy machine learning pipelines and CI/CD processes at scale

Skills Needed

• Minimum 3 years of experience as Machine Learning Engineer
• Knowledge of machine learning and statistics
• Strong experience working in the areas of time series analysis, reinforcement learning, NLP, optimization and heuristics based implementation to solve real-world problems
• Experienced in architecting solutions with Continuous Integration and Continuous Delivery in mind
• Strong knowledge of coding in Python and libraries such as Pandas, Numpy, Scikit-Learn, PyTorch, etc.
• Experience handling Big Data leveraging technologies like Snowflake, Spark. Ability to work in a big data ecosystem - expert in SQL and ability to work in distributed databases.
• Able to refactor data science code and has collaborated with data scientists in developing ML solutions.
• Experience playing the role of full-stack data scientist and taking solutions to production.
• Educational qualifications should be preferably in Computer Science, Statistics, Engineering or a related area.

Job Description

The applicant must have a minimum of 5 years of hands-on IT experience, working on a full software lifecycle in Agile mode.

Good to have experience in data modeling and/or systems architecture.
Responsibilities will include technical analysis, design, development and perform enhancements.

You will participate in all/most of the following activities:
- Working with business analysts and other project leads to understand requirements.
- Modeling and implementing database schemas in DB2 UDB or other relational databases.
- Designing, developing, maintaining and Data processing using Python, DB2, Greenplum, Autosys and other technologies

Skills /Expertise Required :

Work experience in developing large volume database (DB2/Greenplum/Oracle/Sybase).

Good experience in writing stored procedures, integration of database processing, tuning and optimizing database queries.

Strong knowledge of table partitions, high-performance loading and data processing.
Good to have hands-on experience working with Perl or Python.
Hands on development using Spark / KDB / Greenplum platform will be a strong plus.
Designing, developing, maintaining and supporting Data Extract, Transform and Load (ETL) software using Informatica, Shell Scripts, DB2 UDB and Autosys.
Coming up with system architecture/re-design proposals for greater efficiency and ease of maintenance and developing software to turn proposals into implementations.

Need to work with business analysts and other project leads to understand requirements.
Strong collaboration and communication skills

• 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 Snowflake Cloud Datawarehouse as well as SQL and Azure ‘big data’ technologies
• 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 centers 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.

• 3+ years of experience in a Data Engineer or Software 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 “Snowflake Cloud Datawarehouse”
• Experience with Azure cloud services: ADLS, ADF, ADLA, AAS
• Experience with data pipeline and workflow management tools
• 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 Datawarehouse (DWH) systems, and migration from DWH to data lakes/Snowflake
• Understanding of ELT and ETL patterns and when to use each. Understanding of data models and transforming data into the models
• Strong analytic skills related to working with unstructured datasets
• Build processes supporting data transformation, data structures, metadata, dependency and workload management
• Experience supporting and working with cross-functional teams in a dynamic environment.

Responsibilities: 

• Identify complex business problems and work towards building analytical solutions in-order to create large business impact.
• Demonstrate leadership through innovation in software and data products from ideation/conception through design, development and ongoing enhancement, leveraging user research techniques, traditional data tools, and techniques from the data science toolkit such as predictive modelling, NLP, statistical analysis, vector space modelling, machine learning etc.
• Collaborate and ideate with cross-functional teams to identify strategic questions for the business that can be solved and champion the effectiveness of utilizing data, analytics, and insights to shape business.
• Contribute to company growth efforts, increasing revenue and supporting other key business outcomes using analytics techniques.
• Focus on driving operational efficiencies by use of data and analytics to impact cost and employee efficiency.
• Baseline current analytics capability, ensure optimum utilization and continued advancement to stay abridge with industry developments.
• Establish self as a strategic partner with stakeholders, focused on full innovation system and fully supportive of initiatives from early stages to activation.
• Review stakeholder objectives and team's recommendations to ensure alignment and understanding.
• Drive analytics thought leadership and effectively contributes towards transformational initiatives.
• Ensure accuracy of data and deliverables of reporting employees with comprehensive policies and processes.