Machine Learning Engineer

A Delhi NCR based Applied AI & Consumer Tech company tackling one of the largest unsolved consumer internet problems of our time. We are a motley crew of smart, passionate and nice people who believe you can build a high performing company with a culture of respect aka a sports team with a heart aka a caring meritocracy.

Our illustrious angels include unicorn founders, serial entrepreneurs with exits, tech & consumer industry stalwarts and investment professionals/bankers.

We are hiring for our founding team (in Delhi NCR only, no remote) that will take the product from prototype to a landing! Opportunity for disproportionate non-linear impact, learning and wealth creation in a classic 0-1 with a Silicon Valley caliber founding team.

Key Responsibilities:

1.   Data Strategy and Vision:

·       Develop and drive the company's data analytics strategy, aligning it with overall business goals.

·       Define the vision for data analytics, outlining clear objectives and key results (OKRs) to measure success.

2.   Data Analysis and Interpretation:

·       Oversee the analysis of complex datasets to extract valuable insights, trends, and patterns.

·       Utilize statistical methods and data visualization techniques to present findings in a clear and compelling manner to both technical and non-technical stakeholders.

3.   Data Infrastructure and Tools:

·       Evaluate, select, and implement advanced analytics tools and platforms to enhance data processing and analysis capabilities.

·       Collaborate with IT teams to ensure a robust and scalable data infrastructure, including data storage, retrieval, and security protocols.

4.   Collaboration and Stakeholder Management:

·       Collaborate cross-functionally with teams such as marketing, sales, and product development to identify opportunities for data-driven optimizations.

·       Act as a liaison between technical and non-technical teams, ensuring effective communication of data insights and recommendations.

5.   Performance Measurement:

·       Establish key performance indicators (KPIs) and metrics to measure the impact of data analytics initiatives on business outcomes.

·       Continuously assess and improve the accuracy and relevance of analytical models and methodologies.

Qualifications:

• Bachelor's or Master's degree in Data Science, Statistics, Computer Science, or related field.
• Proven experience (5+ years) in data analytics, with a focus on leading analytics teams and driving strategic initiatives.
• Proficiency in data analysis tools such as Python, R, SQL, and advanced knowledge of data visualization tools.
• Strong understanding of statistical methods, machine learning algorithms, and predictive modelling techniques.
• Excellent communication skills, both written and verbal, to effectively convey complex findings to diverse audie 

Job Description:

The data science team is responsible for solving business problems with complex data. Data complexity could be characterized in terms of volume, dimensionality and multiple touchpoints/sources. We understand the data, ask fundamental-first-principle questions, apply our analytical and machine learning skills to solve the problem in the best way possible. 

Our ideal candidate

The role would be a client facing one, hence good communication skills are a must. 

The candidate should have the ability to communicate complex models and analysis in a clear and precise manner. 

The candidate would be responsible for:

• Comprehending business problems properly - what to predict, how to build DV, what value addition he/she is bringing to the client, etc.
• Understanding and analyzing large, complex, multi-dimensional datasets and build features relevant for business
• Understanding the math behind algorithms and choosing one over another
• Understanding approaches like stacking, ensemble and applying them correctly to increase accuracy

Desired technical requirements

• Proficiency with Python and the ability to write production-ready codes. 
• Experience in pyspark, machine learning and deep learning
• Big data experience, e.g. familiarity with Spark, Hadoop, is highly preferred
• Familiarity with SQL or other databases.

Data Engineer 

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 

Familiar with the MicroStrategy architecture, Admin Certification Preferred

· Familiar with administrative functions, using Object Manager, Command Manager, installation/configuration of MSTR in clustered architecture, applying patches, hot-fixes

· Monitor and manage existing Business Intelligence development/production systems

· MicroStrategy installation, upgrade and administration on Windows and Linux platform

· Ability to support and administer multi-tenant MicroStrategy infrastructure including server security troubleshooting and general system maintenance.

· Analyze application and system logs while troubleshooting and root cause analysis

· Work on operations like deploy and manage packages, User Management, Schedule Management, Governing Settings best practices, database instance and security configuration.

· Monitor, report and investigate solutions to improve report performance.

· Continuously improve the platform through tuning, optimization, governance, automation, and troubleshooting.

· Provide support for the platform, report execution and implementation, user community and data investigations.

· Identify improvement areas in Environment hosting and upgrade processes.

· Identify automation opportunities and participate in automation implementations

· Provide on-call support for Business Intelligence issues

· Experience of working on MSTR 2021, MSTR 2021 including knowledge of working on Enterprise Manager and new features like Platform Analytics, Hyper Intelligence, Collaboration, MSTR Library, etc.

· Familiar with AWS, Linux Scripting

· Knowledge of MSTR Mobile

· Knowledge of capacity planning and system’s scaling needs

• Proficiency in shell scripting
• Proficiency in automation of tasks
• Proficiency in Pyspark/Python
• Proficiency in writing and understanding of sqoop
• Understanding of CloudEra manager
• Good understanding of RDBMS
• Good understanding of Excel

1. Proven experience with deploying and tuning Open Source components into enterprise ready production tooling Experience with datacentre (Metal as a Service – MAAS) and cloud deployment technologies (AWS or GCP Architect certificates required)
2. Deep understanding of Linux from kernel mechanisms through user space management
3. Experience on CI/CD (Continuous Integrations and Deployment) system solutions (Jenkins).
4. Using Monitoring tools (local and on public cloud platforms) Nagios, Prometheus, Sensu, ELK, Cloud Watch, Splunk, New Relic etc. to trigger instant alerts, reports and dashboards.  Work closely with the development and infrastructure teams to analyze and design solutions with four nines (99.99%) up-time, globally distributed, clustered, production and non-production virtualized infrastructure. 
5. Wide understanding of IP networking as well as data centre infrastructure

1. Expert with software development tools and sourcecode management, understanding, managing issues, code changes and grouping them into deployment releases in a stable and measurable way to maximize production Must be expert at developing and using ansible roles and configuring deployment templates with jinja2.
2. Solid understanding of data collection tools like Flume, Filebeat, Metricbeat, JMX Exporter agents.
3. Extensive experience operating and tuning the kafka streaming data platform, specifically as a message queue for big data processing
4. Strong understanding and must have experience:
5. Apache spark framework, specifically spark core and spark streaming, 
6. Orchestration platforms, mesos and kubernetes, 
7. Data storage platforms, elasticstack, carbon, clickhouse, cassandra, ceph, hdfs
8. Core presentation technologies kibana, and grafana.
9. Excellent scripting and programming skills (bash, python, java, go, rust). Must have previous experience with “rust” in order to support, improve in house developed products

Red Hat Certified Architect certificate or equivalent required CCNA certificate required 3-5 years of experience running open source big data platforms