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Vetted data scientist 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.
JP Morgan Chase
Vetted data scientist in India (UTC+6)
Hello, Hope you are well. I have an overall experience of 7+ years mostly in Financial industry solving business problems using data. I have experience in Data Science, Data Engineering and Analytics. Currently i am working with Goldman Sachs, previously i have worked with American Express, Fractal Analytics and Infosys.
Goldman Sachs
Vetted data scientist in India (UTC+6)
Meet Harsh, a dedicated member of the Applied AI Engineering team at Target, with a focus on implementing the genAI components using Vertex AI, OpenAI and open source models. This includes working extensively with Foundation Model APIs, Search and Conversation, Model Garden, and Vector Search. My role allows me the opportunity to leverage the latest and most advanced models and products from the Generative AI community. Harsh was engaged in building a MLOps platform from scratch by building abstraction layers with scalable APIs. Proficient in Python, AWS, GCP, Spring Boot, Java, Scala, Kafka, PyTorch, TensorFlow, Flask, FastAPI, React, and Docker, Harsh's expertise spans a wide range of technologies. He is a professional introvert who thrives on writing to learn and continually seeks new knowledge every day. Harsh's fascination with Data Science stems from his mathematical captivation and love for questioning existing processes and assumptions. He excels in developing novel methods and analytical algorithms, constantly striving for consistent improvement. His proficiency in Machine Learning encompasses various algorithms, including Decision Trees, Regression, Classification, Neural Networks, Ensemble methods, Kernel Methods, SVMs, Markov Decision Processes, Game Theory, and Bayesian Learning. Additionally, Harsh has a strong grasp of statistical techniques such as Regression Analysis, Time Series Forecasting, Hypothesis Testing, and A/B Testing. He is experienced in working with applications and databases like Tableau, GitHub, Power BI, Qlik, MySQL, PostgreSQL, Apache Spark, AWS Redshift, DynamoDB, Cassandra, and Hive. Harsh's multifaceted personality shines through in his work and social interactions. As a machine learning enthusiast and sociable individual, he excels in client-facing roles, actively engaging with stakeholders to understand their needs and provide effective solutions. His passion for crunching numbers and working with datasets, alongside creating compelling visualizations, enables him to reveal the stories hidden within the data. Harsh firmly believes in empathy and gratitude, fostering positive work environments and delivering outstanding results. He places great importance on clear communication and defining requirements meticulously to ensure the team achieves the desired outcomes. Outside of work, Harsh cherishes meeting new people, engaging in meaningful conversations, and building valuable relationships. This trait complements his networking skills, making him a valuable asset in both professional and social spheres.
Target
Vetted data scientist in India (UTC+6)
I am a Senior Data Scientist with 6+ years of experience in projects involving Gen AI deep learning, user insights, and biometric identification systems. Proficient in Python, TensorFlow, and various cloud platforms. TECHNICAL SKILLS □ Languages: Python (Numpy, Pandas, Jupyter, OpenCV, Scipy, Flask, Fast API, Plotly), SQL/HQL. PySpark □ Deep Learning and ML models: TensorFlow, Keras, PyTorch, fast.ai, LightGBM, XGBoost, Scikit-Learn □ Others: GCP, Azure, Docker, Kubernetes, PySpark, Conda, Git, MLflow, JMeter, Linux Bash
Walmart
Vetted data scientist in India (UTC+6)
Software engineer with experience in machine learning, backend and frontend development. Leveraging my wide range of expertise to build high impact products.
SAP
Vetted data scientist 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.
Oracle
Vetted data scientist in India (UTC+6)
6 years of experience in building and managing AI Systems. * I develop end-to-end AI systems from requirements analysis, and data gathering to deployment, implementing new methods/research papers, and turning projects into research outcomes. I have achieved substantial performance in DL/ML/RL models for CV and NLP domain problems. * Implementing and deploying projects handling and maintaining scalability, research papers as well as POCs. * Project planning, requirements gathering, and analysing requirements to define the system's architecture, and implementation timeline. * Provide mentoring to junior developers for ML projects. Website: [roshantanisha.github.io/?ref=codementor](http://roshantanisha.github.io/?ref=codementor) Summary: I like to work on technology that is smart, simple and sophisticated. This sums up the vast knowledge required to work on projects to excel in a working product. I like to train Deep Neural Networks and understand them well. I have mentored many students for their AI careers, teaching them Machine Learning and Mathematics. I am a mentor for the RFS (Reach for the Stars) Programme by the Aga Khan Education Board for India. I am an alumnus of this program as well. I have a cumulative experience of 6 years working in the product and service-based industry for creating Machine Learning projects. I have done some innovative work that I am proud of and am continuing to do so. I try my best to contribute my expertise to the project I am working on. Highly Experienced in Machine Learning, Deep Learning, Advanced Deep Learning, Artificial Intelligence, and Algorithms, including models in the production environment, and deploying ML models. Working with top Indian colleges like BITS, niche NLP and CV, real-estate startups, MNCs, and Fortune top 20 companies, working with sensitive anonymized datasets, and creating state-of-the-art models are some of my achievements. I have strong and correct knowledge of Deep Learning concepts from the above experiences.
Vetted data scientist in India (UTC+6)
Innovative Artificial Intelligence Engineer with 6+ years of professional experience in application design, development, testing & deployment. Highly experienced in writing codes & algorithms and equipped with excellent mathematical, and statistical understanding. Possess an unbridled passion for AI and is tenacious in pursuing solutions through advanced computer vision & deep learning techniques.
Vetted data scientist in India (UTC+6)
I’m a Machine Learning Engineer with 7 years of professional experience in Performance Optimisations in Ads, NLP and Operations Efficiency. I have built NLP models using python, pytorch, docker, kubernetes which were used by many Fortune 500 companies. Worked on a performance optisation problem in advertising which resulted in pending patent and 5MM$+ annual revenue. My tech stack comprises Python, Pytorch, Jupyter, Huggingface, MongoDB, CI/CD, Helm, Docker, Kubernetes, Unix, Git. I’ve worked across various industries in a fast-paced environment with a strong sense of ownership.
Vetted data scientist in India (UTC-7)
Data Scientist with 4.9 years of experience in Predictive Modelling and Statistical Research using Python and various Data Visualization tools. Knowledge of various Machine Learning and Deep Learning algorithms such as Regression, Classification, Clustering, Neural Networks and NLP. Uncovering new areas of applications in Insurance and Finance domain with Data Science and Machine Learning and eager to apply this knowledge in other domains as well.
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FAQs
Why hire a data scientist?
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 a data scientist, 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 data scientists can help keep your website up-to-date.
How do I hire data scientists?
To hire a data scientist, 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 data scientists effectively and efficiently. Hire full-time data scientists 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 data scientists 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 data scientists.
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 data scientists for your company, and let Arc handle the logistics.
Where do I hire the best remote data scientists?
There are two types of platforms you can hire data scientists 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 data scientists 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 data scientists, consider niche platforms like Arc that naturally attract and carefully vet their data scientists for hire. This way, you’ll save time and related hiring costs by only interviewing the most suitable remote data scientists.
Some factors to consider when you hire data scientists 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 data scientists for hire.
How do I write a data scientist job description?
Writing a good data scientist job description is crucial in helping you hire data scientists 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 data scientist 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 data scientists, read our Engineer Job Description Guide & Templates.
What skills should I look for in a data scientist?
The top five technical skills data scientists should possess include proficiency in programming languages, understanding data structures and algorithms, experience with databases, familiarity with version control systems, and knowledge of 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 data scientists 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 data scientists to keep up with evolving technology and requirements.
What kinds of data scientists are available for hire through Arc?
You can find a variety of data scientists for hire on Arc! At Arc, you can hire on a freelance, full-time, part-time, or contract-to-hire basis. For freelance data scientists, Arc matches you with the right senior developer in roughly 72 hours. As for full-time remote data scientists 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 engineers in various different time zones and countries for you to choose from.
Lastly, our remote-ready data scientists 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 data scientists?
Arc is trusted by hundreds of startups and tech companies around the world, and we’ve matched thousands of skilled data scientists with both freelance and full-time jobs. We’ve successfully helped Silicon Valley startups and larger tech companies like Spotify and Automattic hire data scientists.
Every data scientist 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 data scientist 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 data scientist's skills?
Arc has a rigorous and transparent vetting process for all types of developers. To become a vetted data scientist 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 data scientists, 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 data scientists, you can rest assured that all remote data scientists 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 data scientists on Arc?
Arc pre-screens all of our remote data scientists before we present them to you. As such, all the remote data scientists 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 data scientist in 72 hours, or find a full-time data scientist 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 data scientists.
How much does a freelance data scientist charge per hour?
Depending on the freelance developer job board you use, freelance remote data scientists' hourly rates can vary drastically. For instance, if you're looking on general marketplaces like Upwork and Fiverr, you can find data scientists 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 data scientists 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 data scientist?
According to the U.S. Bureau of Labor Statistics, the medium annual wage for 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 data scientist’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 data scientists, check out our FAQs page.