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For software developers, learning programming languages needs to be practical. This is where the startup has helped more than 15000 students to turn theory into practical knowledge. Currently, offering 9 courses the startup has played a catalyst for thousands of students to land jobs at tech giants like Google, Amazon, Adobe, and Walmart. The startup enables students to follow a comprehensive curriculum and seek help from industry experts without facing any geological barrier.
The founders of the startup are the alumnus of acclaimed institutes like IIT Delhi and Stanford University with experience of working in Amazon, Facebook, Cars24, and other top startups in India.
- Managing a team of 3-4 content developers working to create course content and projects
- Designing the course content curriculum based on the industry requirements and in interaction with industry experts
- Establishing the required guidelines and processes for the team to follow while creating the content
- Training, reviewing and guiding content developers on the content work that needs to be accomplished adhering to the timelines
What you need to have:
- BE/ B.tech/ BCA/ M.Tech/ MCA with a computer science background
- Excellent problem-solving and team management skills.
- Minimum 3 years of experience working in the data science domain/ edtech content creation
- Exposure to Machine learning algorithms and working on Kaggle projects is preferred
- Ability to do a detailed review of the course content and design project problem statements
- Ability to train and guide a team of content developers to manage timelines and brainstorming on course content
Job Responsibilities
- Design machine learning systems
- Research and implement appropriate ML algorithms and tools
- Develop machine learning applications according to requirements
- Select appropriate datasets and data representation methods
- Run machine learning tests and experiments
- Perform statistical analysis and fine-tuning using test results
- Train and retrain systems when necessary
Requirements for the Job
- Bachelor’s/Master's/PhD in Computer Science, Mathematics, Statistics or equivalent field andmust have a minimum of 2 years of overall experience in tier one colleges
- Minimum 1 year of experience working as a Data Scientist in deploying ML at scale in production
- Experience in machine learning techniques (e.g. NLP, Computer Vision, BERT, LSTM etc..) andframeworks (e.g. TensorFlow, PyTorch, Scikit-learn, etc.)
- Working knowledge in deployment of Python systems (using Flask, Tensorflow Serving)
- Previous experience in following areas will be preferred: Natural Language Processing(NLP) - Using LSTM and BERT; chatbots or dialogue systems, machine translation, comprehension of text, text summarization.
- Computer Vision - Deep Neural Networks/CNNs for object detection and image classification, transfer learning pipeline and object detection/instance segmentation (Mask R-CNN, Yolo, SSD).
Job Description:
The data science team is responsible for solving business problems with complex data. Data complexity could be characterized in terms of volume, dimensionality and multiple touchpoints/sources. We understand the data, ask fundamental-first-principle questions, apply our analytical and machine learning skills to solve the problem in the best way possible.
Our ideal candidate
The role would be a client facing one, hence good communication skills are a must.
The candidate should have the ability to communicate complex models and analysis in a clear and precise manner.
The candidate would be responsible for:
- Comprehending business problems properly - what to predict, how to build DV, what value addition he/she is bringing to the client, etc.
- Understanding and analyzing large, complex, multi-dimensional datasets and build features relevant for business
- Understanding the math behind algorithms and choosing one over another
- Understanding approaches like stacking, ensemble and applying them correctly to increase accuracy
Desired technical requirements
- Proficiency with Python and the ability to write production-ready codes.
- Experience in pyspark, machine learning and deep learning
- Big data experience, e.g. familiarity with Spark, Hadoop, is highly preferred
- Familiarity with SQL or other databases.
along with metrics to track their progress
Managing available resources such as hardware, data, and personnel so that deadlines
are met
Analysing the ML algorithms that could be used to solve a given problem and ranking
them by their success probability
Exploring and visualizing data to gain an understanding of it, then identifying
differences in data distribution that could affect performance when deploying the model
in the real world
Verifying data quality, and/or ensuring it via data cleaning
Supervising the data acquisition process if more data is needed
Defining validation strategies
Defining the pre-processing or feature engineering to be done on a given dataset
Defining data augmentation pipelines
Training models and tuning their hyper parameters
Analysing the errors of the model and designing strategies to overcome them
Deploying models to production
Job Description
We are looking for a data scientist that will help us to discover the information hidden in vast amounts of data, and help us make smarter decisions to deliver even better products. Your primary focus will be in applying data mining techniques, doing statistical analysis, and building high quality prediction systems integrated with our products.
Responsibilities
- Selecting features, building and optimizing classifiers using machine learning techniques
- Data mining using state-of-the-art methods
- Extending company’s data with third party sources of information when needed
- Enhancing data collection procedures to include information that is relevant for building analytic systems
- Processing, cleansing, and verifying the integrity of data used for analysis
- Doing ad-hoc analysis and presenting results in a clear manner
- Creating automated anomaly detection systems and constant tracking of its performance
Skills and Qualifications
- Excellent understanding of machine learning techniques and algorithms, such as Linear regression, SVM, Decision Forests, LSTM, CNN etc.
- Experience with Deep Learning preferred.
- Experience with common data science toolkits, such as R, NumPy, MatLab, etc. Excellence in at least one of these is highly desirable
- Great communication skills
- Proficiency in using query languages such as SQL, Hive, Pig
- Good applied statistics skills, such as statistical testing, regression, etc.
- Good scripting and programming skills
- Data-oriented personality