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 machine learning engineer on the team, you will
• Help science and product teams innovate in developing and improving end-to-end
solutions to machine learning-based security/privacy control
• Partner with scientists to brainstorm and create new ways to collect/curate data
• Design and build infrastructure critical to solving problems in privacy-preserving machine
• Help team self-organize and follow machine learning best practice.
• 4+ years of experience contributing to the architecture and design (architecture, design
patterns, reliability and scaling) of new and current systems
• 4+ years of programming experience with at least one modern language such as Java,
C++, or C# including object-oriented design
• 4+ years of professional software development experience
• 4+ years of experience as a mentor, tech lead OR leading an engineering team
• 4+ years of professional software development experience in Big Data and Machine
• Knowledge of common ML frameworks such as Tensorflow, PyTorch
• Experience with cloud provider Machine Learning tools such as AWS SageMaker
• Programming experience with at least two modern language such as Python, Java, C++,
or C# including object-oriented design
• 3+ years of experience contributing to the architecture and design (architecture, design
patterns, reliability and scaling) of new and current systems
• Experience in python
• BS in Computer Science or equivalent
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.
Job Title: Data Warehouse/Redshift Admin
AWS Redshift Cluster Planning
AWS Redshift Cluster Maintenance
AWS Redshift Cluster Security
AWS Redshift Cluster monitoring.
Experience managing day to day operations of provisioning, maintaining backups, DR and monitoring of AWS RedShift/RDS clusters
Hands-on experience with Query Tuning in high concurrency environment
Expertise setting up and managing AWS Redshift
AWS certifications Preferred (AWS Certified SysOps Administrator)
-Expertise in building AWS Data Engineering pipelines with AWS Glue -> Athena -> Quick sight.
-Experience in developing lambda functions with AWS Lambda.
Expertise with Spark/PySpark
– Candidate should be hands on with PySpark code and should be able to do transformations with Spark
-Should be able to code in Python and Scala.
Snowflake experience will be a plus
Strong knowledge in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, etc.
Sound Knowlegde querying databases and using statistical computer languages: R, Python, SQL, etc.
Strong understanding creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc.
Outplay is building the future of sales engagement, a solution that helps sales teams personalize at scale while consistently staying on message and on task, through true multi-channel outreach including email, phone, SMS, chat and social media. Outplay is the only tool your sales team will ever need to crush their goals. Funded by Sequoia - Headquartered in the US. Sequoia not only led a $2 million seed round in Outplay early this year, but also followed with $7.3 million Series - A recently. The team is spread remotely all over the globe.
Perks of being an Outplayer :
• Fully remote job - You can be on the mountains or at the beach, and still work with us. Outplay is a 100% remote company.
• Flexible work hours - We believe mental health is way more important than a 9-5 job.
• Health Insurance - We are a family, and we take care of each other - we provide medical insurance coverage to all employees and their family members. We also provide an additional benefit of doctor consultation along with the insurance plan.
• Annual company retreat - we work hard, and we party harder.
• Best tools - we buy you the best tools of the trade
• Celebrations - No, we never forget your birthday or anniversary (be it work or wedding) and we never leave an opportunity to celebrate milestones and wins.
• Safe space to innovate and experiment
• Steady career growth and job security
About the Role:
We are looking for a Senior Data Scientist to help research, develop and advance the charter of AI at Outplay and push the threshold of conversational intelligence.
Job description :
• Lead AI initiatives that dissects data for creating new feature prototypes and minimum viable products
• Conduct product research in natural language processing, conversation intelligence, and virtual assistant technologies
• Use independent judgment to enhance product by using existing data and building AI/ML models
• Collaborate with teams, provide technical guidance to colleagues and come up with new ideas for rapid prototyping. Convert prototypes into scalable and efficient products.
• Work closely with multiple teams on projects using textual and voice data to build conversational intelligence
• Prototype and demonstrate AI augmented capabilities in the product for customers
• Conduct experiments to assess the precision and recall of language processing modules and study the effect of such experiments on different application areas of sales
• Assist business development teams in the expansion and enhancement of a feature pipeline to support short and long-range growth plans
• Identify new business opportunities and prioritize pursuits of AI for different areas of conversational intelligence
• Build reusable and scalable solutions for use across a varied customer base
• Participate in long range strategic planning activities designed to meet the company’s objectives and revenue goals
Required Skills :
• Bachelors or Masters in a quantitative field such as Computer Science, Statistics, Mathematics, Operations Research or related field with focus on applied Machine Learning, AI, NLP and data-driven statistical analysis & modelling.
• 4+ years of experience applying AI/ML/NLP/Deep Learning/ data-driven statistical analysis & modelling solutions to multiple domains. Experience in the Sales and Marketing domain is a plus.
• Experience in building Natural Language Processing (NLP), Conversational Intelligence, and Virtual Assistants based features.
• Excellent grasp on programming languages like Python. Experience in GoLang would be a plus.
• Proficient in analysis using python packages like Pandas, Plotly, Numpy, Scipy, etc.
• Strong and proven programming skills in machine learning and deep learning with experience in frameworks such as TensorFlow/Keras, Pytorch, Transformers, Spark etc
• Excellent communication skills to explain complex solutions to stakeholders across multiple disciplines.
• Experience in SQL, RDBMS, Data Management and Cloud Computing (AWS and/or Azure) is a plus.
• Extensive experience of training and deploying different Machine Learning models
• Experience in monitoring deployed models to proactively capture data drifts, low performing models, etc.
• Exposure to Deep Learning, Neural Networks or related fields
• Passion for solving AI/ML problems for both textual and voice data.
• Fast learner, with great written and verbal communication skills, and be able to work independently as
well as in a team environment
In 2020, Renew Power, India’s largest renewables developer, acquired Climate Connect. Following ReNew’s listing on NASDAQ in summer 2021, Climate Connect has become the technology anchor of a new fully independent subsidiary - Climate Connect Digital. With backing from ReNew as the anchor investor to pursue an ambitious and visionary new strategy for rapid organic and inorganic growth.
Our mission has technology at its core and involves unlocking value through intelligent software, digitalisation, and ‘horizontal integration’ across the energy ecosystem. However, computational power and machine learning in the energy sector have yet to be fully leveraged and can create massive value.
We are looking for people with knowledge of:
● Excellent verbal communications, including the ability to clearly and concisely articulate complex concepts to both technical and non-technical collaborators
● Demonstrated history of knowledge in Computer Science, Statistics, Mathematics, Software Engineering or related technical fields
● Industry experience with proven ability to apply scientific methods to solve real-world problems on large scale data
● Extensive experience with Python and SQL for software development, data analysis, and machine learning
● Experience on Libraries: TensorFlow, Keras, Numpy, sklearn, pandas, scikit-image, matplotlib, Jupyter, Statsmodels
● Experience on Time Series analysis, including EDA, Statistical inferences, ARIMA, GARCH
● Knowledge of Cluster Analysis, Classification Trees, Discriminant Analysis, Neural Networks, Deep Learning, Logistic Regression, Associations Analysis
● Hands-on experience in implementing Deep learning models with video and time series data (CNN, LSTM- s, Aotoencoder, RBM)
● Experience of Regression, Multicriteria Decision Making, Descriptive Statistics, Hypothesis Testing, Segmentation/ Classification, Predictive Analytics
● Aptitude and experience in applied statistics and machine learning techniques
● Firm grasp of visualization tools interactive and self-serving such as business intelligence and notebooks
● Experience launching production-quality machine learning models at scale e.g. dataset construction, preprocessing, deployment, monitoring, quality assurance
● Experience with math programming is an added advantage. For example: optimization, computational geometry, numerical linear algebra, etc.
What you’ll work on:
We are developing a marketing automation platform through which an electricity retailer may apply a suite of proprietary ML algorithms to optimize outcomes across a range of channels and touchpoints. We require the services of a data science professional who can design and implement various AI/ML models that optimize the performance, quality, and reliability of the product. This position offers a potential pathway to leading an entire ML expert team. These are a few things you can look forward to working on:
● Translating high-level problems and key objectives into granular model requirements.
● Defining acceptance criteria that are well structured, detailed, and comprehensive.
● Developing and testing algorithms using our price forecasts, and customers' energy portfolio.
● Collaborating with the software engineering team in deploying the developed models tailored to specific customer needs.
● Participating in the software development process, and doing the required testing, and debugging to support the deployed models.
● Taking responsibility for ensuring tracking of appropriate events/metrics, so that monitoring is timely and rigorous.
● Driving the response to the discovery of regressions or failures, by undertaking various exercises (e.g. debugging, RCA, etc.) as needed
● 6-11 years of experience in the field of Data Sciences or Machine Learning Qualifications:
● B.E / B. Tech / M. Tech / PhD in CS/IT or Data Sciences
What’s in it for you
We offer competitive salaries based on prevailing market rates. In addition to your introductory package, you can expect to receive the following benefits:
Flexible working hours
Unlimited annual leaves
Learning and development budget
Medical insurance/Term insurance, Gratuity benefits over and above the salaries
Access to industry and domain thought leaders
At Climate Connect Digital, you get a rare opportunity to join an established company at the early stages of a significant and well-backed global growth push.
Link to apply - https://climateconnect.digital/careers/?jobId=gaG9dgeTYBvF
What you will be doing:
As a part of the Global Credit Risk and Data Analytics team, this person will be responsible for carrying out analytical initiatives which will be as follows: -
- Dive into the data and identify patterns
- Development of end-to-end Credit models and credit policy for our existing credit products
- Leverage alternate data to develop best-in-class underwriting models
- Working on Big Data to develop risk analytical solutions
- Development of Fraud models and fraud rule engine
- Collaborate with various stakeholders (e.g. tech, product) to understand and design best solutions which can be implemented
- Working on cutting-edge techniques e.g. machine learning and deep learning models
Example of projects done in past:
- Lazypay Credit Risk model using CatBoost modelling technique ; end-to-end pipeline for feature engineering and model deployment in production using Python
- Fraud model development, deployment and rules for EMEA region
- 1-3 years of work experience as a Data scientist (in Credit domain)
- 2016 or 2017 batch from a premium college (e.g B.Tech. from IITs, NITs, Economics from DSE/ISI etc)
- Strong problem solving and understand and execute complex analysis
- Experience in at least one of the languages - R/Python/SAS and SQL
- Experience in in Credit industry (Fintech/bank)
- Familiarity with the best practices of Data Science
Add-on Skills :
- Experience in working with big data
- Solid coding practices
- Passion for building new tools/algorithms
- Experience in developing Machine Learning models