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Top Anomaly Detection developers available to hire:

Freelance Anomaly Detection developers - Yevgeniy D.
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Yevgeniy D.

Vetted Anomaly Detection developer in the United States (UTC-5)

Dedicated Data Scientist/Applied Research Scientist with over 8 years of experience, with a strong background in causal inference, data science, program evaluation, data analytics, risk analytics, reporting, and predictive modeling. Passionate about leveraging data to drive informed decision-making and skilled in using a variety of methodologies and technologies to extract actionable insights from complex datasets.

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Freelance Anomaly Detection developers - Christian N.
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Christian N.

Vetted Anomaly Detection developer in Germany (UTC+2)

I have a background in theoretical physics and have worked on machine learning and data science-related topics since 2016. Since then, I have published multiple peer-reviewed papers on machine learning as part of the autonomous driving unit at Mercedes Benz AG and worked as a data science consultant/developer for DAX-listed companies. Others would describe me as creative in my thinking, excelling at finding new ways to tackle problems. I love intellectual challenges that keep me engaged and thrive in cooperative working environments. I am a very self-directed person who can quickly identify what needs to be done and act accordingly. On top of that, my strengths are communicating complex ideas at an appropriate level and holding engaging presentations.

Freelance Anomaly Detection developers - Suman D.
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Suman D.

Vetted Anomaly Detection developer in India (UTC+6)

I am a Senior Data Scientist with over 9 years of experience in leveraging advanced AI, machine learning, and deep learning techniques to solve complex business challenges across industries like banking, retail, manufacturing, and technology. My expertise lies in designing scalable solutions that drive measurable outcomes, optimize processes, and empower organizations to make data-driven decisions. Currently, at JPMorgan Chase & Co., I lead initiatives that have delivered significant business value, including developing an unsupervised payment risk detection model that mitigated fraud risks and saved $24M globally. I also spearheaded the creation of a Retrieval-Augmented Generation (RAG) framework to enhance enterprise-wide information retrieval and knowledge generation. My work on standardizing LLM evaluation frameworks has improved cross-functional collaboration and ensured consistency in model performance metrics. Previously, at Walmart Global Tech India, I contributed to sustainability goals by building multi-model machine learning systems for EV charging station recommendations while driving store revenue growth. I also implemented transformer-based models for product categorization and price standardization. At Tiger Analytics, I developed real-time predictive maintenance systems that saved $50M annually for a global steel manufacturer and improved inventory forecasting accuracy by over 20%. With a strong foundation in programming languages like Python and SQL, libraries such as PyTorch and LangChain, and expertise in cloud platforms like AWS SageMaker and GCP BigQuery, I specialize in cutting-edge technologies like Large Language Models (LLMs), Natural Language Processing (NLP), anomaly detection, and MLOps. My academic projects further showcase my ability to innovate in areas like federated learning for DocVQA, RAG frameworks for better retrieval-generation pipelines, and prompt compression for optimized token utilization. Beyond my professional achievements, I am dedicated to mentoring aspiring AI professionals through Scaler Academy and sharing insights as a tech blogger at KnowledgeHut. My mission is to harness the power of AI to create meaningful impact while fostering growth in the AI community.

Freelance Anomaly Detection developers - Sumit K.
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Sumit K.

Vetted Anomaly Detection developer in India (UTC+6)

Data Scientist with 6.5 years of expertise in ML, NLP, and deep learning. Proficient in Python, R, and SQL, skilled in intricate data analysis, visualization, and statistical modeling. Proficiency in Generative AI tools like LangChain, seamlessly integrating it with ChatGPT, Pinecone, LLAMA 2, and Hugging Face for dynamic language-based applications. Strong problem-solving abilities, excelling in fast-paced environments.

Freelance Anomaly Detection developers - david C.
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david C.

Vetted Anomaly Detection developer in Brazil (UTC-3)

Experienced Data Scientist with 5+ years in AI-driven solutions, with expertise in computer vision and time-series analysis. Currently working at Itaú Unibanco, the largest bank in Brazil, where I optimize the accounting pipeline and develop anomaly detection models for debit and credit transactions across the entire financial system. Previously, I led projects in medical imaging, infrastructure assessment, and industrial automation using AI. Passionate about solving complex problems and driving innovation in international environments.

Freelance Anomaly Detection developers - Zubair A.
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Zubair A.

Vetted Anomaly Detection developer in Pakistan (UTC-7)

Results-oriented Senior Machine Learning Engineer with a proven track record of delivering impactful AI solutions that drive business growth. Specializing in the development and deployment of cutting-edge algorithms, I have successfully enhanced customer churn prediction, boosted customer satisfaction scores, and improved fraud detection systems. Skilled in analyzing large datasets to design personalized recommendation engines and optimize machine learning pipelines for real-time data processing. My expertise extends to developing and fine-tuning Large Language Models (LLMs), implementing Agentic Retrieval-Augmented Generation (RAG) systems, and building intelligent chatbots to elevate natural language understanding, automate customer interactions, and simplify access to critical documentation. These systems go beyond traditional query-response mechanisms by providing context-aware, dynamic, and actionable insights. Passionate about integrating state-of-the-art technologies to maximize model performance and operational efficiency. I consistently leverage my ability to research, innovate, and implement data-driven strategies that lead to measurable, game-changing outcomes. Always eager to push the boundaries of AI to deliver strategic value, transform business operations, and revolutionize user engagement through intelligent automation.

Freelance Anomaly Detection developers - Juan R.
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Juan R.

Vetted Anomaly Detection developer in Colombia (UTC-5)

I am a Graduate in Applied Mathematics and Computer Science with a strong background in data science. Throughout my career, I've demonstrated the ability to develop innovative machine learning solutions that drive strategic business objectives. Now, I seek to take my experience to the next level, becoming an expert in deep learning technologies, such as LLMs and Computer Vision, to solve complex business problems. My results-oriented approach, my advanced technical skills as well as soft skills like problem solving, team-work and effective communication make me an ideal candidate for a AI / Machine Learning Engineering roles.

Freelance Anomaly Detection developers - Umair P.
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Umair P.

Vetted Anomaly Detection developer in New Zealand (UTC+13)

Experienced AI leader with a Ph.D. in ML and over 9 years of hands-on experience implementing and deploying AI solutions. Successfully led teams to deliver innovative projects on tight deadlines, resulting in a 40% increase in user engagement and a 30% reduction in workplace accidents. Demonstrated expertise in project management, driving organizational optimization, and streamlining project delivery, achieving a 30% reduction in time-to-market for ML models across various domains in just 12 months.

Freelance Anomaly Detection developers - Leonardo F.
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Leonardo F.

Vetted Anomaly Detection developer in Brazil (UTC-3)

With 5 years of experience in data engineering technologies, I am skilled in Data Analysis, Data Quality, and Big Data. I have a strong understanding of Hadoop, NoSQL, and Spark ecosystems, enabling me to develop scalable and reliable solutions for large-scale data management. Additionally, I have the ability to integrate Machine Learning technologies into Big Data solutions.

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Why clients hire Anomaly Detection developers with Arc

Without Arc by my side, I would be wasting a lot of time looking for and vetting talent. I'm not having to start a new talent search from scratch. Instead, I’m able to leverage the talent pool that Arc has created.
Mitchum Owen
Mitchum Owen
President of Milo Digital
The process of filling our position took less than a week and they found us a superstar. They've had the flexibility to meet our specific needs every step of the way and their customer service has been top-notch since day one.
Matt Gysel
Matt Gysel
Finance & Strategy at BaseVenture
The biggest advantage and benefit of working with Arc is the tremendous reduction in time spent sourcing quality candidates. We’re able to identify the talent in a matter of days.
Philip Tsai
Philip Tsai
Director of Engineering at Chegg

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FAQs

Why hire an Anomaly Detection developer?

In today’s world, most companies have code-based needs that require developers to help build and maintain. For instance, if your business has a website or an app, you’ll need to keep it updated to ensure you continue to provide positive user experiences. At times, you may even need to revamp your website or app. This is where hiring a developer becomes crucial.

Depending on the stage and scale of your product and services, you may need to hire an Anomaly Detection developer, multiple engineers, or even a full remote developer team to help keep your business running. If you’re a startup or a company running a website, your product will likely grow out of its original skeletal structure. Hiring full-time remote Anomaly Detection developers can help keep your website up-to-date.

How do I hire Anomaly Detection developers?

To hire an Anomaly Detection developer, you need to go through a hiring process of defining your needs, posting a job description, screening resumes, conducting interviews, testing candidates’ skills, checking references, and making an offer.

Arc offers three services to help you hire Anomaly Detection developers effectively and efficiently. Hire full-time Anomaly Detection developers from a vetted candidates pool, with new options every two weeks, and pay through prepaid packages or per hire. Alternatively, hire the top 2.3% of expert freelance Anomaly Detection developers in 72 hours, with weekly payments.

If you’re not ready to commit to the paid plans, our free job posting service is for you. By posting your job on Arc, you can reach up to 450,000 developers around the world. With that said, the free plan will not give you access to pre-vetted Anomaly Detection developers.

Furthermore, we’ve partnered with compliance and payroll platforms Deel and Remote to make paperwork and hiring across borders easier. This way, you can focus on finding the right Anomaly Detection developers for your company, and let Arc handle the logistics.

Where do I hire the best remote Anomaly Detection developers?

There are two types of platforms you can hire Anomaly Detection developers from: general and niche marketplaces. General platforms like Upwork, Fiverr, and Gigster offer a variety of non-vetted talents unlimited to developers. While you can find Anomaly Detection developers on general platforms, top tech talents generally avoid general marketplaces in order to escape bidding wars.

If you’re looking to hire the best remote Anomaly Detection developers, consider niche platforms like Arc that naturally attract and carefully vet their Anomaly Detection developers for hire. This way, you’ll save time and related hiring costs by only interviewing the most suitable remote Anomaly Detection developers.

Some factors to consider when you hire Anomaly Detection developers include the platform’s specialty, developer’s geographical location, and the service’s customer support. Depending on your hiring budget, you may also want to compare the pricing and fee structure.

Make sure to list out all of the important factors when you compare and decide on which remote developer job board and platform to use to find Anomaly Detection developers for hire.

How do I write an Anomaly Detection developer job description?

Writing a good Anomaly Detection developer job description is crucial in helping you hire Anomaly Detection developers that your company needs. A job description’s key elements include a clear job title, a brief company overview, a summary of the role, the required duties and responsibilities, and necessary and preferred experience. To attract top talent, it's also helpful to list other perks and benefits, such as flexible hours and health coverage.

Crafting a compelling job title is critical as it's the first thing that job seekers see. It should offer enough information to grab their attention and include details on the seniority level, type, and area or sub-field of the position.

Your company description should succinctly outline what makes your company unique to compete with other potential employers. The role summary for your remote Anomaly Detection developer should be concise and read like an elevator pitch for the position, while the duties and responsibilities should be outlined using bullet points that cover daily activities, tech stacks, tools, and processes used.

For a comprehensive guide on how to write an attractive job description to help you hire Anomaly Detection developers, read our Software Engineer Job Description Guide & Templates.

What skills should I look for in an Anomaly Detection developer?

The top five technical skills Anomaly Detection developers should possess include proficiency in programming languages, understanding data structures and algorithms, experience with databases, familiarity with version control systems, and knowledge of software testing and debugging.

Meanwhile, the top five soft skills are communication, problem-solving, time management, attention to detail, and adaptability. Effective communication is essential for coordinating with clients and team members, while problem-solving skills enable Anomaly Detection developers to analyze issues and come up with effective solutions. Time management skills are important to ensure projects are completed on schedule, while attention to detail helps to catch and correct issues before they become bigger problems. Finally, adaptability is crucial for Anomaly Detection developers to keep up with evolving technology and requirements.

What kinds of Anomaly Detection developers are available for hire through Arc?

You can find a variety of Anomaly Detection developers for hire on Arc! At Arc, you can hire on a freelance, full-time, part-time, or contract-to-hire basis. For freelance Anomaly Detection developers, Arc matches you with the right senior developer in roughly 72 hours. As for full-time remote Anomaly Detection developers for hire, you can expect to make a successful hire in 14 days. To extend a freelance engagement to a full-time hire, a contract-to-hire fee will apply.

In addition to a variety of engagement types, Arc also offers a wide range of developers located in different geographical locations, such as Latin America and Eastern Europe. Depending on your needs, Arc offers a global network of skilled software engineers in various different time zones and countries for you to choose from.

Lastly, our remote-ready Anomaly Detection developers for hire are all mid-level and senior-level professionals. They are ready to start coding straight away, anytime, anywhere.

Why is Arc the best choice for hiring Anomaly Detection developers?

Arc is trusted by hundreds of startups and tech companies around the world, and we’ve matched thousands of skilled Anomaly Detection developers with both freelance and full-time jobs. We’ve successfully helped Silicon Valley startups and larger tech companies like Spotify and Automattic hire Anomaly Detection developers.

Every Anomaly Detection developer for hire in our network goes through a vetting process to verify their communication abilities, remote work readiness, and technical skills. Additionally, HireAI, our GPT-4-powered AI recruiter, enables you to get instant candidate matches without searching and screening.

Not only can you expect to find the most qualified Anomaly Detection developer on Arc, but you can also count on your account manager and the support team to make each hire a success. Enjoy a streamlined hiring experience with Arc, where we provide you with the developer you need, and take care of the logistics so you don’t need to.

How does Arc vet a Anomaly Detection developer's skills?

Arc has a rigorous and transparent vetting process for all types of developers. To become a vetted Anomaly Detection developer for hire on Arc, developers must pass a profile screening, complete a behavioral interview, and pass a technical interview or pair programming.

While Arc has a strict vetting process for its verified Anomaly Detection developers, if you’re using Arc’s free job posting plan, you will only have access to non-vetted developers. If you’re using Arc to hire Anomaly Detection developers, you can rest assured that all remote Anomaly Detection developers have been thoroughly vetted for the high-caliber communication and technical skills you need in a successful hire.

How long does it take to find Anomaly Detection developers on Arc?

Arc pre-screens all of our remote Anomaly Detection developers before we present them to you. As such, all the remote Anomaly Detection developers you see on your Arc dashboard are interview-ready candidates who make up the top 2% of applicants who pass our technical and communication assessment. You can expect the interview process to happen within days of posting your jobs to 450,000 candidates. You can also expect to hire a freelance Anomaly Detection developer in 72 hours, or find a full-time Anomaly Detection developer that fits your company’s needs in 14 days.

Here’s a quote from Philip, the Director of Engineering at Chegg:

“The biggest advantage and benefit of working with Arc is the tremendous reduction in time spent sourcing quality candidates. We’re able to identify the talent in a matter of days.”

Find out more about how Arc successfully helped our partners in hiring remote Anomaly Detection developers.

How much does a freelance Anomaly Detection developer charge per hour?

Depending on the freelance developer job board you use, freelance remote Anomaly Detection developers' hourly rates can vary drastically. For instance, if you're looking on general marketplaces like Upwork and Fiverr, you can find Anomaly Detection developers for hire at as low as $10 per hour. However, high-quality freelance developers often avoid general freelance platforms like Fiverr to avoid the bidding wars.

When you hire Anomaly Detection developers through Arc, they typically charge between $60-100+/hour (USD). To get a better understanding of contract costs, check out our freelance developer rate explorer.

How much does it cost to hire a full time Anomaly Detection developer?

According to the U.S. Bureau of Labor Statistics, the medium annual wage for software developers in the U.S. was $120,730 in May 2021. What this amounts to is around $70-100 per hour. Note that this does not include the direct cost of hiring, which totals to about $4000 per new recruit, according to Glassdoor.

Your remote Anomaly Detection developer’s annual salary may differ dramatically depending on their years of experience, related technical skills, education, and country of residence. For instance, if the developer is located in Eastern Europe or Latin America, the hourly rate for developers will be around $75-95 per hour.

For more frequently asked questions on hiring Anomaly Detection developers, check out our FAQs page.

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