Data Science Jobs
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Most Demanding Data Analytics Skills!

↳ Dive into the essential skills and tools that are shaping the future of data analytics. From SQL and Python to Tableau and PowerBI, discover which technologies are crucial for advancing your data analysis capabilities.

↳ Explore the importance of machine learning techniques like linear regression, logistic regression, SVM, decision trees, random forests, K-means, and K-nearest neighbors, and how they can enhance your analytical prowess.

↳ Understand why soft skills such as communication, collaboration, critical thinking, and creativity are just as important as technical skills in the data analytics field.

↳ Get a comprehensive overview of the skills and technologies that can propel your career forward and make you a standout in the competitive world of data analytics.
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Role: Data Scientist - GenAI
Experience: 2 - 4 Years
NP: Immediate - 60 days
Location: 6th Floor, Resulticks Edge Solution, Greems Road,
Thousand Lights, Chennai - 600006

Date : 12th April ( 10:00 AM - 12:30 PM )

Primary Skills:
GenAI, LLM, Python, Pandas, Flask, API, Cloud ( GCP, AWZ or Azure) &
Data Visualization

Contact person: Nivetha N - 9176250701 (n.nivetha@resulticks.com)
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Forwarded from Python for Data Analysts
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https://jobs.careers.microsoft.com/global/en/job/1818159/Data-Scientist

Microsoft Hiring for Data Scientist Roles in US for all levels and locations!
Zycus is hiring AI Engineer

For 2021, 2022, 2023, 2024 gards
Location: Multiple

https://zycus.sensehq.com/careers/jobs/56968
Neural Networks and Deep Learning
Neural networks and deep learning are integral parts of artificial intelligence (AI) and machine learning (ML). Here's an overview:

1.Neural Networks: Neural networks are computational models inspired by the human brain's structure and functioning. They consist of interconnected nodes (neurons) organized in layers: input layer, hidden layers, and output layer.

Each neuron receives input, processes it through an activation function, and passes the output to the next layer. Neurons in subsequent layers perform more complex computations based on previous layers' outputs.

Neural networks learn by adjusting weights and biases associated with connections between neurons through a process called training. This is typically done using optimization techniques like gradient descent and backpropagation.

2.Deep Learning : Deep learning is a subset of ML that uses neural networks with multiple layers (hence the term "deep"), allowing them to learn hierarchical representations of data.

These networks can automatically discover patterns, features, and representations in raw data, making them powerful for tasks like image recognition, natural language processing (NLP), speech recognition, and more.

Deep learning architectures such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Long Short-Term Memory networks (LSTMs), and Transformer models have demonstrated exceptional performance in various domains.

3.Applications Computer Vision: Object detection, image classification, facial recognition, etc., leveraging CNNs.

Natural Language Processing (NLP) Language translation, sentiment analysis, chatbots, etc., utilizing RNNs, LSTMs, and Transformers.
Speech Recognition: Speech-to-text systems using deep neural networks.

4.Challenges and Advancements: Training deep neural networks often requires large amounts of data and computational resources. Techniques like transfer learning, regularization, and optimization algorithms aim to address these challenges.

LAdvancements in hardware (GPUs, TPUs), algorithms (improved architectures like GANs - Generative Adversarial Networks), and techniques (attention mechanisms) have significantly contributed to the success of deep learning.

5. Frameworks and Libraries: There are various open-source libraries and frameworks (TensorFlow, PyTorch, Keras, etc.) that provide tools and APIs for building, training, and deploying neural networks and deep learning models.

Join for more: https://t.me/machinelearning_deeplearning
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Forwarded from Python for Data Analysts
𝟱 𝗣𝗼𝘄𝗲𝗿𝗳𝘂𝗹 𝗙𝗿𝗲𝗲 𝗔𝗜 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝗳𝗿𝗼𝗺 𝗛𝗮𝗿𝘃𝗮𝗿𝗱 & 𝗦𝘁𝗮𝗻𝗳𝗼𝗿𝗱😍

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Airtel is hiring Growth Analyst 🚀

Experience : 1+ Year
Location : Gurugram

Apply link : Check out this job at airtel: https://www.linkedin.com/jobs/view/4206005779
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𝟯 𝗙𝗿𝗲𝗲 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝘁𝗼 𝗟𝗲𝘃𝗲𝗹 𝗨𝗽 𝗬𝗼𝘂𝗿 𝗧𝗲𝗰𝗵 𝗦𝗸𝗶𝗹𝗹𝘀 𝗶𝗻 𝟮𝟬𝟮𝟱😍

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Company Name: Zycus
Job Role: AI Engineer
Location: Mumbai, Pune, Bengaluru

Apply Link: https://zycus.sensehq.com/careers/jobs/56968

Limited Time Opportunities.
Share with your friends, colleagues, and college groups!

Thank You ❤️
Atlassian hiring Senior Data Scientist - Machine Learning

Location: Remote

Apply link: https://careers-apac-atlassian.icims.com/jobs/17213/senior-data-scientist---machine-learning/job?iis=LinkedIn&iisn=LinkedIn_Job_Ad&mode=job

Requirements:

5+ years of experience in Data Science or related fields

Expertise in applying a broad variety of ML methods including NLP and LLM to solve business problems using large amounts of data

Proven track record of delivering ML projects end-to-end, including designing, development, deployment and monitoring

Ability to communicate and explain data science concepts to diverse audiences, craft a compelling story

Expertise in programming languages such as Python or Java with and the ability to write performant code, familiarity with SQL, knowledge of Spark and cloud data environments (e.g. AWS, Databricks)

Agile development mindset, appreciating the benefit of constant iteration and improvement

👉WhatsApp Channel: https://whatsapp.com/channel/0029Vaxjq5a4dTnKNrdeiZ0J

👉Telegram Link: https://t.me/addlist/4q2PYC0pH_VjZDk5

All the best 👍👍
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𝗔𝗜 & 𝗠𝗟 𝗙𝗥𝗘𝗘 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 😍

Qualcomm—a global tech giant offering completely FREE courses that you can access anytime, anywhere.

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Clustrex Data Private Limited is hiring AI/ML Engineer

For 2023, 2024, 2025 gards
Location: Chennai

https://www.linkedin.com/jobs/view/4207922559
Forwarded from Data Analyst Jobs
Amgen is hiring Associate Data Scientist 🚀

Qualification : Bachelor's degree
Experience : 0-3 Years
Location : Hyderabad

Apply link : https://careers.amgen.com/job/-/-/87/79374246176?src=Linkedin

👉WhatsApp Channel: https://whatsapp.com/channel/0029Vaxjq5a4dTnKNrdeiZ0J

👉Telegram Link: https://t.me/addlist/4q2PYC0pH_VjZDk5

All the best 👍👍
LTIMindtree is looking for a Data Scientist who will support building AI tools for customers The candidate should be skilled at using large data sets to find opportunities for product and process optimization The candidate must have a proven ability to drive business results with their databased insights The candidate must be comfortable working with a wide range of stakeholders and functional teams

Primary Skills Python, AI, ML (Machine Learning) Gen AI – Generative AI + RAG, NLP, LLM, Deep Learning, Computer Vision, AWS, Cloud Or Azure Open AI (Any Cloud)

Experience- 5 to 16 Years

FACE 2 FACE DRIVE - MUMBAI (POWAI)
DATE - 12TH MARCH 2025

If anyone is interested please share your updated resume on email id - Devyani.Pillai2@ltimindtree.com
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Capital One hiring Senior Manager, Machine Learning Engineering

Location: Bengalore

Link: https://capitalone.wd12.myworkdayjobs.com/Capital_One/job/Bangalore-In/Senior-Manager--Machine-Learning-Engineering_R211489
𝗝𝗣 𝗠𝗼𝗿𝗴𝗮𝗻 𝗙𝗥𝗘𝗘 𝗩𝗶𝗿𝘁𝘂𝗮𝗹 𝗜𝗻𝘁𝗲𝗿𝗻𝘀𝗵𝗶𝗽 𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝘀😍

JPMorgan offers free virtual internships to help you develop industry-specific tech, finance, and research skills. 

- Software Engineering Internship
- Investment Banking Program
- Quantitative Research Internship
 
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Complete Roadmap to land a Data Scientist job in 2025

Phase 1: Build Foundations (3-6 months)

1. Learn Python programming basics
2. Understand statistics and mathematics concepts (linear algebra, calculus, probability)
3. Familiarize yourself with data visualization tools (Matplotlib, Seaborn)

Phase 2: Data Science Skills (6-9 months)

1. Master machine learning algorithms (scikit-learn, TensorFlow)
2. Learn data manipulation frameworks (Pandas, NumPy)
3. Study data visualization libraries (Plotly, Bokeh)
4. Understand database management systems (SQL, NoSQL)

Phase 3: Practice and Projects (3-6 months)

1. Work on personal projects (Kaggle competitions, datasets)
2. Participate in data science communities (GitHub, Reddit)
3. Build a portfolio showcasing skills

Phase 4: Job Preparation (1-3 months)

1. Update resume and online profiles (LinkedIn)
2. Practice whiteboarding and coding interviews
3. Prepare answers for common data science questions

Best Resources to learn Data Science 👇👇

Python Tutorial

Data Science Course by Kaggle

Machine Learning Course by Google

Best Data Science & Machine Learning Resources

Interview Process for Data Science Role at Amazon

Python Interview Resources

Join @free4unow_backup for more free courses

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ENJOY LEARNING👍👍
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