Staff Analytics Engineer at AlphaSense

New Delhi, Delhi, India

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Not SpecifiedCompensation

Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Technology, Market Intelligence, AIIndustries

Requirements

Bachelor's (or Master’s) degree in Computer Science, Information Systems, or a closely related discipline
5+ years of experience as an Analytics Engineer
Overall solid programming skills, able to write modular, maintainable code in Python
Experience in creating data pipelines and transforming data using SQL in GCP
Experience in creating Tableau workbooks
Experience in working with AWS Services like S3, SNS, SQS, and AWS Lambda Function
Experience in Kubernetes and CI/CD Process
Experience in working with NoSQL DBs (e.g. MongoDB, DynamoDB)
Experience in working with event-driven systems
Familiarity with Agile methodologies and product development processes
Excellent communication and collaboration skills

Responsibilities

Develop R&D Analytical Data Lake for real-time data ingestion, storage, processing and analytics on BI tools
Develop and maintain data pipelines required for the extraction, transformation, cleaning, pre-processing, aggregation, and loading of data from a wide variety of data sources using Python and SQL
Develop Tableau dashboards by establishing connections with GCP and other tools

Skills

Key technologies and capabilities for this role

PythonGoogle Cloud PlatformGCPETLData PipelinesEngineering Platforms

Questions & Answers

Common questions about this position

What are the key required skills for the Staff Analytics Engineer role?

The role requires proficiency in Python for setting up engineering platforms and data pipelines, experience with Google Cloud Platform (GCP) for ETLs and SQL data transformation, hands-on experience designing Tableau workbooks, plus skills in AWS services (S3, SNS, SQS, Lambda), Kubernetes, CI/CD, NoSQL databases like MongoDB and DynamoDB, and event-driven systems.

What is the salary or compensation for this position?

This information is not specified in the job description.

Is this role remote or does it require office work?

This information is not specified in the job description.

What is the company culture like at AlphaSense?

The Global Product Analytics team values innovation, execution, delivery, learning, growth, and a 'roll up your sleeves and do whatever it takes' attitude, with a mission to empower decision-makers through trusted data and scalable analytics.

What makes a strong candidate for this Staff Analytics Engineer position?

A strong candidate has a Bachelor's or Master’s degree in Computer Science or related field, 5+ years as an Analytics Engineer, solid Python programming skills for modular code, and experience across data pipelines, GCP, Tableau, AWS, Kubernetes, CI/CD, NoSQL, and event-driven systems, plus familiarity with Scrum Agile and an energetic attitude.

AlphaSense

AI-driven financial research platform

About AlphaSense

AlphaSense provides a financial research platform that uses artificial intelligence to help clients gain insights into various companies, industries, and market trends. Users can search through a vast library of over 300 million documents, which includes both external and proprietary content. The AI technology streamlines the research process by automating repetitive tasks, allowing clients to concentrate on analyzing the information instead. Additionally, AlphaSense monitors real-time data to highlight important insights, helping clients stay ahead in a rapidly changing market. Unlike its competitors, AlphaSense is particularly focused on data security, implementing advanced measures like the zero trust security model and secure data encryption. The goal of AlphaSense is to empower clients in making informed decisions, whether they are launching new products or providing strategic insights to executives.

New York City, New YorkHeadquarters

2011Year Founded

$1,248.2MTotal Funding

LATE_VCCompany Stage

Cybersecurity, AI & Machine Learning, Financial ServicesIndustries

1,001-5,000Employees

Benefits

Company Equity

Performance Bonus

Remote Work Options

Risks

Rapid AI adoption may homogenize creative outputs, reducing unique value of insights.

Tegus acquisition poses integration challenges, potentially disrupting service delivery.

Reliance on AI exposes AlphaSense to risks of biases and inaccuracies affecting client trust.

Differentiation

AlphaSense leverages AI to provide real-time insights, enhancing decision-making speed and accuracy.

The platform's Generative Search tool offers advanced search capabilities mimicking human analysts.

AlphaSense's acquisition of Tegus expands its content library, offering unmatched insights.

Upsides

Generative AI integration enhances AlphaSense's speed and reliability of financial insights.

The Tegus acquisition significantly expands AlphaSense's content library for comprehensive insights.

AI-driven tools are essential for financial institutions, aligning with AlphaSense's offerings.

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