2. Build large datasets that will be used to train the models
3. Empirically evaluate related research works
4. Train and evaluate deep learning architectures on multiple large scale datasets
5. Collaborate with the rest of the research team to produce high-quality research
About CarWale: CarWale's mission is to bring delight in car buying, we offer a bouquet of reliable tools and services to help car consumers decide on buying the right car, at the right price and from the right partner. CarWale has always strived to serve car buyers and owners in the most comprehensive and convenient way possible. We provide a platform where car buyers and owners can research, buy, sell and come together to discuss and talk about their cars.We aim to empower Indian consumers to make informed car buying and ownership decisions with exhaustive and un-biased information on cars through our expert reviews, owner reviews, detailed specifications and comparisons. We understand that a car is by and large the second-most expensive asset a consumer associates his lifestyle with! Together with CarTrade & BikeWale, we are the market leaders in the personal mobility media space.About the Team:We are a bunch of enthusiastic analysts assisting all business functions with their data needs. We deal with huge but diverse datasets to find relationships, patterns and meaningful insights. Our goal is to help drive growth across the organization by creating a data-driven culture.
We are looking for an experienced Data Scientist who likes to explore opportunities and know their way around data to build world class solutions making a real impact on the business.
Skills / Requirements –
- 3-5 years of experience working on Data Science projects
- Experience doing statistical modelling of big data sets
- Expert in Python, R language with deep knowledge of ML packages
- Expert in fetching data from SQL
- Ability to present and explain data to management
- Knowledge of AWS would be beneficial
- Demonstrate Structural and Analytical thinking
- Ability to structure and execute data science project end to end
Bachelor’s degree in a quantitative field (Maths, Statistics, Computer Science). Masters will be preferred.
As a Data Science Lead, you will manage multiple consulting projects of varying complexity and ensure on-time and on-budget delivery for clients. You will lead a team of data scientists and collaborate across cross-functional groups, while contributing to new business development, supporting strategic business decisions and maintaining & strengthening client base
- Work with team to define business requirements, come up with analytical solution and deliver the solution with specific focus on Big Picture to drive robustness of the solution
- Work with teams of smart collaborators. Be responsible for their appraisals and career development.
- Participate and lead executive presentations with client leadership stakeholders.
- Be part of an inclusive and open environment. A culture where making mistakes and learning from them is part of life
- See how your work contributes to building an organization and be able to drive Org level initiatives that will challenge and grow your capabilities.
Role & Responsibilities
- Serve as expert in Data Science, build framework to develop Production level DS/AI models.
- Apply AI research and ML models to accelerate business innovation and solve impactful business problems for our clients.
- Lead multiple teams across clients ensuring quality and timely outcomes on all projects.
- Lead and manage the onsite-offshore relation, at the same time adding value to the client.
- Partner with business and technical stakeholders to translate challenging business problems into state-of-the-art data science solutions.
- Build a winning team focused on client success. Help team members build lasting career in data science and create a constant learning/development environment.
- Present results, insights, and recommendations to senior management with an emphasis on the business impact.
- Build engaging rapport with client leadership through relevant conversations and genuine business recommendations that impact the growth and profitability of the organization.
- Lead or contribute to org level initiatives to build the Tredence of tomorrow.
Qualification & Experience
- Bachelor's /Master's /PhD degree in a quantitative field (CS, Machine learning, Mathematics, Statistics, Data Science) or equivalent experience.
- 6-10+ years of experience in data science, building hands-on ML models
- Expertise in ML – Regression, Classification, Clustering, Time Series Modeling, Graph Network, Recommender System, Bayesian modeling, Deep learning, Computer Vision, NLP/NLU, Reinforcement learning, Federated Learning, Meta Learning.
- Proficient in some or all of the following techniques: Linear & Logistic Regression, Decision Trees, Random Forests, K-Nearest Neighbors, Support Vector Machines ANOVA , Principal Component Analysis, Gradient Boosted Trees, ANN, CNN, RNN, Transformers.
- Knowledge of programming languages SQL, Python/ R, Spark.
- Expertise in ML frameworks and libraries (TensorFlow, Keras, PyTorch).
- Experience with cloud computing services (AWS, GCP or Azure)
- Expert in Statistical Modelling & Algorithms E.g. Hypothesis testing, Sample size estimation, A/B testing
- Knowledge in Mathematical programming – Linear Programming, Mixed Integer Programming etc , Stochastic Modelling – Markov chains, Monte Carlo, Stochastic Simulation, Queuing Models.
- Experience with Optimization Solvers (Gurobi, Cplex) and Algebraic programming Languages(PulP)
- Knowledge in GPU code optimization, Spark MLlib Optimization.
- Familiarity to deploy and monitor ML models in production, delivering data products to end-users.
- Experience with ML CI/CD pipelines.
We are looking for a Data Scientist to analyze large amounts of raw information to find patterns that will help improve our company. We will rely on you to build data products to extract valuable business insights.
In this role, you should be highly analytical with a knack for analysis, math and statistics. Critical thinking and problem-solving skills are essential for interpreting data. We also want to see a passion for machine-learning and research.
Your goal will be to help our company analyze trends to make better decisions.
1. 2 to 4 years of relevant industry experience
2. Experience in Linear algebra, statistics & Probability skills, such as distributions, Deep Learning, Machine Learning
3. Strong mathematical and statistics background is a must
4. Experience in machine learning frameworks such as Tensorflow, Caffe, PyTorch, or MxNet
5. Strong industry experience in using design patterns, algorithms and data structures
6. Industry experience in using feature engineering, model performance tuning, and optimizing machine learning models
7. Hands on development experience in Python and packages such as NumPy, Sci-Kit Learn and Matplotlib
8. Experience in model building, hyper
PriceLabs ( chicagobusiness.com/innovators/what-if-you-could-adjust-prices-meet-demand ) is a cloud based software for vacation and short term rentals to help them dynamically manage prices just the way large hotels and airlines do! Our mission is to help small businesses in the travel and tourism industry by giving them access to advanced analytical systems that are often restricted to large companies.
We're looking for someone with strong analytical capabilities who wants to understand how our current architecture and algorithms work, and help us design and develop long lasting solutions to address those. Depending on the needs of the day, the role will come with a good mix of team-work, following our best practices, introducing us to industry best practices, independent thinking, and ownership of your work.
- Design, develop and enhance our pricing algorithms to enable new capabilities.
- Process, analyze, model, and visualize findings from our market level supply and demand data.
- Build and enhance internal and customer facing dashboards to better track metrics and trends that help customers use PriceLabs in a better way.
- Take ownership of product ideas and design discussions.
- Occasional travel to conferences to interact with prospective users and partners, and learn where the industry is headed.
- Bachelors, Masters or Ph. D. in Operations Research, Industrial Engineering, Statistics, Computer Science or other quantitative/engineering fields.
- Strong understanding of analysis of algorithms, data structures and statistics.
- Solid programming experience. Including being able to quickly prototype an idea and test it out.
- Strong communication skills, including the ability and willingness to explain complicated algorithms and concepts in simple terms.
- Experience with relational databases and strong knowledge of SQL.
- Experience building data heavy analytical models in the travel industry.
- Experience in the vacation rental industry.
- Experience developing dynamic pricing models.
- Prior experience working at a fast paced environment.
- Willingness to wear many hats.
Responsibilities for Data Scientist/ NLP Engineer
Work with customers to identify opportunities for leveraging their data to drive business
• Develop custom data models and algorithms to apply to data sets.
• Basic data cleaning and annotation for any incoming raw data.
• Use predictive modeling to increase and optimize customer experiences, revenue
generation, ad targeting and other business outcomes.
• Develop company A/B testing framework and test model quality.
• Deployment of ML model in production.
Qualifications for Junior Data Scientist/ NLP Engineer
• BS, MS in Computer Science, Engineering, or related discipline.
• 3+ Years of experience in Data Science/Machine Learning.
• Experience with programming language Python.
• Familiar with at least one database query language, such as SQL
• Knowledge of Text Classification & Clustering, Question Answering & Query Understanding,
Search Indexing & Fuzzy Matching.
• Excellent written and verbal communication skills for coordinating acrossteams.
• Willing to learn and master new technologies and techniques.
• Knowledge and experience in statistical and data mining techniques:
GLM/Regression, Random Forest, Boosting, Trees, text mining, NLP, etc.
• Experience with chatbots would be bonus but not required
Octro Inc. is looking for a Data Scientist who will support the product, leadership and marketing teams with insights gained from analyzing multiple sources of data. The ideal candidate is adept at using large data sets to find opportunities for product and process optimization and using models to test the effectiveness of different courses of action.
They must have strong experience using a variety of data mining/data analysis methods, using a variety of data tools, building and implementing models, using/creating algorithms and creating/running simulations. They must have a proven ability to drive business results with their data-based insights.
They must be comfortable working with a wide range of stakeholders and functional teams. The right candidate will have a passion for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes.
- Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
- Mine and analyze data from multiple databases to drive optimization and improvement of product development, marketing techniques and business strategies.
- Assess the effectiveness and accuracy of new data sources and data gathering techniques.
- Develop custom data models and algorithms to apply to data sets.
- Use predictive modelling to increase and optimize user experiences, revenue generation, ad targeting and other business outcomes.
- Develop various A/B testing frameworks and test model qualities.
- Coordinate with different functional teams to implement models and monitor outcomes.
- Develop processes and tools to monitor and analyze model performance and data accuracy.
- Strong problem solving skills with an emphasis on product development and improvement.
- Advanced knowledge of SQL and its use in data gathering/cleaning.
- Experience using statistical computer languages (R, Python, etc.) to manipulate data and draw insights from large data sets.
- Experience working with and creating data architectures.
- Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
- Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
- Excellent written and verbal communication skills for coordinating across teams.