Technologies
Libraries And Widgets
Developers using SciPy

Developers using SciPy

SciPy is an open-source Python library for scientific and technical computing, providing modules for optimization, linear algebra, integration, interpolation, special functions, FFT, signal and image processing, ODE solvers, and statistical functions.
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Developers using SciPy

NAME
contact
DESIGNATION
COUNTRY
Company
Total tENURE
Anju
Python Developer
United States Country Flag Icon
United States
Google Company Logo
Google
4 years
Alvaro Ortega
Principal Engineer
United Kingdom Country Flag Icon
United Kingdom
Medallia Company Logo
Medallia
19 years
Louis Yang
Machine Learning Engineer
United States Country Flag Icon
United States
The TJX Companies, Inc. Company Logo
The TJX Companies, Inc.
13 years
Geoff Langenderfer
Software Engineer
United States Country Flag Icon
United States
Salesforce Company Logo
Salesforce
6 years
Walter Simson
Senior AI Engineer
United Kingdom Country Flag Icon
United Kingdom
Snowflake Company Logo
Snowflake
6 years
Noah Stier
Senior Autopilot Machine Learning Engineer
Australia Country Flag Icon
Australia
PwC Company Logo
PwC
7 years
Prat Singh
Python Software Developer
United States Country Flag Icon
United States
EY Company Logo
EY
4 years
Armin Rad
Staff Data Scientist
United Kingdom Country Flag Icon
United Kingdom
Google Company Logo
Google
6 years
Mayank K
Senior Cloud Data Engineer
United Kingdom Country Flag Icon
United Kingdom
Birlasoft Company Logo
Birlasoft
4 years
Akhila M
Java Developer
France Country Flag Icon
France
Amazon Web Services Company Logo
Amazon Web Services
7 years
Showing 10 of
33,529
results
Page 1 of
3,353
NAME
contact
DESIGNATION
COUNTRY
Company
Total tENURE
Kyle Prifogle
Senior Data Engineer
United States Country Flag Icon
United States
Fives Company Logo
Fives
12 years
Jesse Lord
Senior Data Engineer
United States Country Flag Icon
United States
NCCI Company Logo
NCCI
7 years
Micah Lyle
CEO
United States Country Flag Icon
United States
SAIC Company Logo
SAIC
6 years
Lou King
Head of Data Integration
United States Country Flag Icon
United States
Offered.ai Company Logo
Offered.ai
3 years
Boris Petersen
Chief Cloud Engineer
Germany Country Flag Icon
Germany
DreamBox Learning Company Logo
DreamBox Learning
11 years
David Ames
Head of DevOps
United Kingdom Country Flag Icon
United Kingdom
Accenture Company Logo
Accenture
3 years
Raghavendar Lokineni
Founder
India Country Flag Icon
India
CrowdStrike Company Logo
CrowdStrike
13 years
Allen Cypher
Chief Software Architect
United States Country Flag Icon
United States
Google Company Logo
Google
34 years
Zheng J
Senior Software Engineer
United States Country Flag Icon
United States
Nagarro Company Logo
Nagarro
7 years
Marty Ballard
Senior Fullstack Engineer
United States Country Flag Icon
United States
Pratt & Whitney Company Logo
Pratt & Whitney
19 years
Showing 10 of
33,529
results
Page 1 of
3,353

Want access to the complete contacts list?

Unlock the full contact information of
33,529
developers actively working with
SciPy
technology, including economic buyers data for each account, complete with verified contact information, role tenure, company context, and adoption signals.
Book a Demo
View Companies

Companies using SciPy

Technology
is any of
SciPy Technology Logo/Icon
SciPy
company
COUNTRY
Tech confidence score
REVENUE
# Tech JOB POSTINGS
Amazon
United States Country Flag Icon
United States
-
4,167
Anduril Industries
United States Country Flag Icon
United States
$34M
1,132
Blue Yonder
United States Country Flag Icon
United States
$125M
489
Capgemini Engineering
France Country Flag Icon
France
-
189

Want access to the complete company list?

Unlock the full database of
8,009
companies actively hiring with
SciPy
technology, including firmographic data,
33,529
developer profiles working on that technology, and direct contacts to engineering leaders within your target accounts.
View All Companies

What would you like to do with developer-level contact data that are users of SciPy?

Build my target developer list or assign economic buyers leads to my sales team

Transform your desired technology user data into actionable sales territories by combining firmographic ICP criteria with real-time technology adoption signals. Traditional account assignment based solely on company size and industry leaves money on the table—successful DevTool sales teams prioritize accounts showing active technology expansion signals.

Strategic account prioritization framework

Building an effective Total Addressable Market (TAM) requires more than basic firmographic filters. Companies using your desired technology represent varying levels of buying intent depending on their implementation stage, team growth, and technology stack evolution. Learn our complete framework for building DevTool ICP account lists to establish the foundation for strategic account segmentation.

Confluent ICP scoring example illustrating core, broader, and relevant universe tiers based on Kafka adoption and data streaming scale

Standard ICP criteria—geography, industry, company size, revenue—only provide baseline qualification. High-performing sales teams layer technology hiring signals on top of firmographic data to identify accounts actively expanding their technical capabilities. Companies hiring  for your desired technology engineers or architects signal active investment in the technology stack, indicating higher purchase intent and budget availability.

In-market account identification and assignment

Priority account assignment should factor in recent technology hiring patterns as a proxy for market timing. Companies posting jobs for Redis engineers, Kubernetes specialists, or React developers demonstrate active technology expansion—making them significantly more likely to evaluate complementary tools within 90 days.

Our LinkedIn outreach playbook details the specific process for identifying and assigning these in-market accounts to sales teams. This approach increases meeting acceptance rates by 40% compared to generic outbound because prospects are already in active buying mode.

Territory assignment best practices

Tier 1 accounts: Companies using your desired technology with recent hiring activity for related roles. These accounts get immediate sales attention with personalized outreach referencing their specific technology initiatives and hiring needs.

Tier 2 accounts: Established desired technology users without recent hiring signals but strong firmographic fit. Assign these accounts for longer-term nurture campaigns and quarterly check-ins to monitor technology expansion signals.

Tier 3 accounts: Companies using your desired technology with weaker ICP fit or unclear expansion signals. Route these accounts to inside sales or marketing-qualified lead campaigns until stronger buying signals emerge.

Refresh account assignments monthly based on new hiring signals and technology adoption data. Companies can move between tiers quickly as their technology needs evolve, and sales territories should reflect these dynamic market conditions rather than static demographic assignments.

The combination of your desired technology usage data and hiring intelligence creates a predictive framework for sales success, ensuring your team focuses energy on accounts most likely to convert within the current quarter.

Learn more

Run marketing Campaigns

Leverage your desired technology user data to create targeted campaigns across three distinct audience levels: companies, developers (practitioners), and economic buyers. Each audience type requires different messaging, channels, and campaign strategies to maximize conversion rates.

Multi-level audience targeting

Companies: Target organizations using your technology of choice for account-based marketing approaches. Focus on company-level signals, firmographics, and technology stack intelligence to build high-intent prospect lists.

Developers (contacts): Reach practitioners who directly implement and use chosen technology. These technical decision-makers influence tool adoption and can become internal champions for your solution.

Economic Buyers (contacts): Target executives and budget holders at companies using your desired technology. While they may not use the technology directly, they control purchasing decisions and strategic technology investments.

Campaign strategies by audience type

ABM Google/LinkedIn Ads to your TOFU audience: Run account-based display campaigns targeting companies using containerization technologies like Docker or Kubernetes. Create awareness-stage content about DevOps optimization, infrastructure costs, or developer productivity to capture early-stage interest from decision-makers.

Invite developers to topical webinars: Host technical webinars for Redis users about database optimization, caching strategies, or microservices architecture. Developers using Redis are likely interested in performance engineering topics that showcase your platform's capabilities in a educational, non-sales context. Leading DevTools like Galileo and Camunda use this strategy effectively—see how they leverage expert-led sessions to grow their TOFU audience by educating and nurturing developer communities around emerging technologies.

LinkedIn outbound campaigns to developers or economic buyers: Execute targeted LinkedIn outreach to practitioners and buyers at companies using complementary technologies. See how Kubegrade leveraged Kubernetes user data to run successful LinkedIn and email campaigns, or follow our proven LinkedIn outreach playbook that helped Unstructured book meetings with economic buyers.

Competitor email campaigns based on competitor technology: Target companies using competing solutions like MongoDB (if you're in the database space) or Elasticsearch (for search solutions). Craft messaging around migration benefits, performance comparisons, or feature gaps that position your solution as the superior alternative.

Complimentary technology campaigns: Run campaigns to companies using GraphQL (if you provide API tools) or React (for frontend development solutions). Focus messaging on how your product enhances their existing technology investments rather than replacing them—creating additive value propositions.

Technical content nurture campaigns to developers: Send regular technical newsletters to PostgreSQL users featuring database optimization tips, query performance guides, or architectural best practices. This builds relationship equity with practitioners who influence purchasing decisions while demonstrating your platform's technical depth.

Campaign execution framework

Each campaign type works best when aligned with the prospect's technology maturity and buying stage. Companies actively expanding their technology usage often have budget allocated for complementary solutions, making them higher-intent prospects than those just beginning adoption.

Combine multiple campaign types for maximum impact: start with educational content to developers, then retarget engaged prospects with ABM campaigns to economic buyers at the same companies. This multi-touch approach increases conversion rates while building relationships across the entire buying committee.

Learn more

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How to target developers using SciPy

How to build your target account list?

Start by building your Ideal Customer Profile (ICP) universe using technology signals as a foundation. Companies using

SciPy

often share similar technical maturity and infrastructure needs, making them prime candidates for developer-focused solutions. Learn our complete framework for building DevTool ICP account lists to maximize your targeting precision.

Customize this data by filtering for geography, industry, company size, revenue, technology usage, job positions and more. Our platform provides technology intelligence at both company and individual levels—categorized into developers/practitioners and economic buyers within those organizations. This dual-layer approach enables precise targeting whether you're running ABM campaigns at the account level or personalized outreach to specific contacts.

Download your refined lists in Excel or CSV format, sync directly to your CRM (HubSpot, Salesforce), or use our APIs to send data to your warehouse. For individual-level targeting, explore our

Companies using

database for direct practitioner and buyer intelligence.

How to get alerted when new developers are working on SciPy technology?

Set up automated alerts to capture companies as they adopt

SciPy

in real-time.

This gives your sales team first-mover advantage when prospects are actively evaluating and implementing new solutions—the optimal time for outreach.

Configure alerts based on your specific ICP criteria: get notified when companies in your target geography, industry, or size range start using your target technology. Alerts are delivered directly to your inbox with complete company and contact intelligence, enabling immediate, contextual outreach while the technology adoption signal is fresh.

How to sync this data with my CRM or sales stack?

Export technology user data seamlessly into your existing sales and marketing infrastructure. Direct CRM integrations with HubSpot and Salesforce automatically sync company and contact records with technology intelligence, enriching your existing database.

Use our API endpoints to send

SciPy

user data directly to your data warehouse, enabling advanced segmentation and analytics across your entire revenue stack. This approach works particularly well for companies running sophisticated ABM programs or complex lead scoring models.

The targeting strategy differs significantly between contact-level outreach and account-based campaigns. For individual targeting, focus on practitioners who directly use

SciPy

with personalized technical messaging. For ABM approaches, target economic buyers at companies using

SciPy

with broader business value propositions and multi-threading strategies.

Frequently Asked Questions (FAQ)

What is SciPy?

SciPy is a cutting-edge technology that falls under the category of Scientific Computing Libraries. It builds on the NumPy array object and is part of the NumPy stack which includes tools like Matplotlib, pandas, and SymPy. Developed in 2001 by scientists seeking to bring advanced mathematical and algorithmic capabilities to Python, SciPy has evolved into a core tool for scientific research, data analysis, and engineering applications. The library provides efficient numerical routines for optimization, integration, interpolation, eigenvalue problems, algebraic equations, differential equations, statistics, and many other classes of problems.

Architecturally, SciPy is organized into subpackages that cover different scientific computing domains. Its core functionality includes scipy.optimize for function minimization and root finding, scipy.linalg for linear algebra operations, scipy.integrate for numerical integration, scipy.signal for signal processing, and scipy.stats for statistical functions and probability distributions. What makes SciPy unique is its combination of Python's readability and ease of use with the computational efficiency of languages like Fortran and C. Many SciPy functions are thin wrappers around industrial-strength implementations written in these lower-level languages, providing both performance and accessibility.

SciPy has seen widespread adoption across academia, research institutions, and industries where scientific computing is essential. It forms the foundation for countless specialized scientific packages in fields ranging from astronomy to machine learning. The library continues to evolve with regular releases, maintaining backward compatibility while adding new algorithms and optimizations. As part of the broader scientific Python ecosystem, SciPy's future outlook remains strong, with ongoing development focused on performance improvements, expanded functionality, and better integration with modern computing paradigms including GPU acceleration and parallel processing.

What is the source of this data?

We aggregate developer & company technographics intelligence from multiple proprietary and partner sources. Our platform monitors job postings across millions of companies—tracking listings on career sites, job boards, and recruitment platforms to identify technology adoption patterns and internal tool usage. This hiring signal data reveals what technologies organizations are actively investing in.

Beyond job data, Reo.Dev maintains a proprietary database of 30+ million developers and tracks activity across public GitHub repositories to capture real-time technology usage signals.

We supplement this with GDPR-compliant datasets from trusted data broker partners and visitor intelligence platforms, creating a comprehensive view of both company-level tech stacks and individual developer behaviors.

This multi-source approach ensures you're working with the most accurate, up-to-date company technographics & developer intelligence available.

How often is the data updated?

Our platform refreshes data daily, giving you access to the latest developer and technology intelligence. This continuous update cycle ensures your go-to-market teams are working with current information that reflects real-time market movements, emerging technology adoption patterns, and fresh hiring signals from across the industry.

How many developers use

SciPy
?
As of now, we have data on
33,529
developers that use
SciPy
.

How to find developers that use

SciPy
?

Visit reo.dev and use Reo.Dev's audience builder to search for developers using your desired technology—our platform analyzes job postings, GitHub repositories, and proprietary developer data to identify the  technology stack for any given organization. Book a demo with us today to get started.

How to get an updated list of developers that use

SciPy
?

Reo.Dev provides real-time access to companies using your desired technology of choice and thousands of other developer technologies. Our platform continuously tracks technology adoption signals from job postings, GitHub activity, and proprietary developer data to give you the most current view of which developers & organizations are actively using the technologies in their tech stack/developer profile. Simply search for your desired technology within our audience builder to generate a targeted list of developers—complete with their current company, seniority, years of experience, and tech stack intelligence at an account level. Book a demo with us today to get access to the latest data.