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Design, implement, and improve the analytics platform
Implement and simplify self-service data query and analysis capabilities of the BI platform
Develop and improve the current BI architecture, emphasizing data security, data quality
and timeliness, scalability, and extensibility
Deploy and use various big data technologies and run pilots to design low latency
data architectures at scale
Collaborate with business analysts, data scientists, product managers, software development engineers,
and other BI teams to develop, implement, and validate KPIs, statistical analyses, data profiling, prediction,
forecasting, clustering, and machine learning algorithms
Educational
At Ganit we are building an elite team, ergo we are seeking candidates who possess the
following backgrounds:
7+ years relevant experience
Expert level skills writing and optimizing complex SQL
Knowledge of data warehousing concepts
Experience in data mining, profiling, and analysis
Experience with complex data modelling, ETL design, and using large databases
in a business environment
Proficiency with Linux command line and systems administration
Experience with languages like Python/Java/Scala
Experience with Big Data technologies such as Hive/Spark
Proven ability to develop unconventional solutions, sees opportunities to
innovate and leads the way
Good experience of working in cloud platforms like AWS, GCP & Azure. Having worked on
projects involving creation of data lake or data warehouse
Excellent verbal and written communication.
Proven interpersonal skills and ability to convey key insights from complex analyses in
summarized business terms. Ability to effectively communicate with multiple teams
Good to have
AWS/GCP/Azure Data Engineer Certification
A Bachelor’s degree in data science, statistics, computer science, or a similar field
2+ years industry experience working in a data science role, such as statistics, machine learning,
deep learning, quantitative financial analysis, data engineering or natural language processing
Domain experience in Financial Services (banking, insurance, risk, funds) is preferred
Have and experience and be involved in producing and rapidly delivering minimum viable products,
results focused with ability to prioritize the most impactful deliverables
Strong Applied Statistics capabilities. Including excellent understanding of Machine Learning
techniques and algorithms
Hands on experience preferable in implementing scalable Machine Learning solutions using Python /
Scala / Java on Azure, AWS or Google cloud platform
Experience with storage frameworks like Hadoop, Spark, Kafka etc
Experience in building &deploying unsupervised, semi-supervised, and supervised models and be
knowledgeable in various ML algorithms such as regression models, Tree-based algorithms,
ensemble learning techniques, distance-based ML algorithms etc
Ability to track down complex data quality and data integration issues, evaluate different algorithmic
approaches, and analyse data to solve problems.
Experience in implementing parallel processing and in-memory frameworks such as H2O.ai
- Develop, train, and optimize machine learning models using Python, ML algorithms, deep learning frameworks (e.g., TensorFlow, PyTorch), and other relevant technologies.
- Implement MLOps best practices, including model deployment, monitoring, and versioning.
- Utilize Vertex AI, MLFlow, KubeFlow, TFX, and other relevant MLOps tools and frameworks to streamline the machine learning lifecycle.
- Collaborate with cross-functional teams to design and implement CI/CD pipelines for continuous integration and deployment using tools such as GitHub Actions, TeamCity, and similar platforms.
- Conduct research and stay up-to-date with the latest advancements in machine learning, deep learning, and MLOps technologies.
- Provide guidance and support to data scientists and software engineers on best practices for machine learning development and deployment.
- Assist in developing tooling strategies by evaluating various options, vendors, and product roadmaps to enhance the efficiency and effectiveness of our AI and data science initiatives.
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
Education –
Bachelor’s degree in a quantitative field (Maths, Statistics, Computer Science). Masters will be preferred.
- 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.
- Mine and analyze data from company 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 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.
- Develop processes and tools to monitor and analyze model performance and data accuracy.
Roles & Responsibilities
- Experience using statistical languages (R, Python, SQL, etc.) to manipulate data and draw insights from large data sets.
- Experience working with and creating data architectures.
- Looking for someone with 3-7 years of experience manipulating data sets and building statistical models
- Has a Bachelor's, Master's in Computer Science or another quantitative field
- Knowledge and experience in statistical and data mining techniques :
- GLM/Regression, Random Forest, Boosting, Trees, text mining,social network analysis, etc.
- Experience querying databases and using statistical computer languages :R, Python, SQL, etc.
- Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees,neural networks, etc.
- Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, Gurobi, MySQL, etc.
- Experience visualizing/presenting data for stakeholders using: Periscope, Business Objects, D3, ggplot, etc.
• Problem Solving:. Resolving production issues to fix service P1-4 issues. Problems relating to
introducing new technology, and resolving major issues in the platform and/or service.
• Software Development Concepts: Understands and is experienced with the use of a wide range of
programming concepts and is also aware of and has applied a range of algorithms.
• Commercial & Risk Awareness: Able to understand & evaluate both obvious and subtle commercial
risks, especially in relation to a programme.
Experience you would be expected to have
• Cloud: experience with one of the following cloud vendors: AWS, Azure or GCP
• GCP : Experience prefered, but learning essential.
• Big Data: Experience with Big Data methodology and technologies
• Programming : Python or Java worked with Data (ETL)
• DevOps: Understand how to work in a Dev Ops and agile way / Versioning / Automation / Defect
Management – Mandatory
• Agile methodology - knowledge of Jira
•3+ years of experience in big data & data warehousing technologies
•Experience in processing and organizing large data sets
•Experience with big data tool sets such Airflow and Oozie
•Experience working with BigQuery, Snowflake or MPP, Kafka, Azure, GCP and AWS
•Experience developing in programming languages such as SQL, Python, Java or Scala
•Experience in pulling data from variety of databases systems like SQL Server, maria DB, Cassandra
NOSQL databases
•Experience working with retail, advertising or media data at large scale
•Experience working with data science engineering, advanced data insights development
•Strong quality proponent and thrives to impress with his/her work
•Strong problem-solving skills and ability to navigate complicated database relationships
•Good written and verbal communication skills , Demonstrated ability to work with product
management and/or business users to understand their needs.
Role & responsibilities:
- Developing ETL pipelines for data replication
- Analyze, query and manipulate data according to defined business rules and procedures
- Manage very large-scale data from a multitude of sources into appropriate sets for research and development for data science and analysts across the company
- Convert prototypes into production data engineering solutions through rigorous software engineering practices and modern deployment pipelines
- Resolve internal and external data exceptions in timely and accurate manner
- Improve multi-environment data flow quality, security, and performance
Skills & qualifications:
- Must have experience with:
- virtualization, containers, and orchestration (Docker, Kubernetes)
- creating log ingestion pipelines (Apache Beam) both batch and streaming processing (Pub/Sub, Kafka)
- workflow orchestration tools (Argo, Airflow)
- supporting machine learning models in production
- Have a desire to continually keep up with advancements in data engineering practices
- Strong Python programming and exploratory data analysis skills
- Ability to work independently and with team members from different backgrounds
- At least a bachelor's degree in an analytical or technical field. This could be applied mathematics, statistics, computer science, operations research, economics, etc. Higher education is welcome and encouraged.
- 3+ years of work in software/data engineering.
- Superior interpersonal, independent judgment, complex problem-solving skills
- Global orientation, experience working across countries, regions and time zones
The Data Engineer would be responsible for selecting and integrating Big Data tools and frameworks required. Would implement Data Ingestion & ETL/ELT processes
Required Experience, Skills and Qualifications:
- Hands on experience on Big Data tools/technologies like Spark, Databricks, Map Reduce, Hive, HDFS.
- Expertise and excellent understanding of big data toolset such as Sqoop, Spark-streaming, Kafka, NiFi
- Proficiency in any of the programming language: Python/ Scala/ Java with 4+ years’ experience
- Experience in Cloud infrastructures like MS Azure, Data lake etc
- Good working knowledge in NoSQL DB (Mongo, HBase, Casandra)
The Job
The Architect, Machine Learning and Artificial Intelligence including Computer Vision will grow and lead a team of talented Machine Learning (ML), Computer Vision (CV) and Artificial Intelligence (AI) researchers and engineers to develop innovative machine learning algorithms, scalable ML system, and AI applications for Racetrack. This role will be focused on developing and deploying personalization and recommender system, search, experimentation, audience, and content AI solutions to drive user experience and growth.
The Daily
- Develop innovative data science solutions that utilize machine learning and deep learning algorithms, statistical and quantitative modelling approaches to support product, engineering, content, and marketing initiatives.
- Build and lead a world-class team of ML and AI scientists and engineers.
- Be a hands-on leader to mentor the team in latest machine learning and deep learning approaches, and to introduce new technologies and processes. Single headedly manage the MVP and PoCs
- Work with ML engineers to design solution architecture and develop scalable machine learning system to accelerate learning cycle.
- Identify data science opportunities that deliver business value.
- Develop ML/AI/CV roadmap and educate both internal and external stakeholders at all levels to drive implementation and measurement.
- Hands on experience in Image processing for auto industry
- BFSI domain knowledge is a plus
- Provide thought leadership to enable ML/AI applications.
- Manage products priorities and ensure timely delivery.
- Develop and evangelize best practices for scoping, building, validating, deploying, and monitoring ML/AI products.
- Prepare and present ML modelling results and analytical insights that help drive the business to senior leadership.
The Essentials
- 8 + years of work experience in Machine Learning, AI and Data Science with a proven track record to drive innovation and business impacts
- 4 + years of managing a team of data scientists, ML and AI researchers and engineers
- Strong machine learning, deep learning, and statistical modelling expertise, such as causal inference modelling, ensembles, neural networks, reinforcement learning, NLP, and computer vision
- Advanced knowledge of SQL and experience with big data platform (AWS, Snowflake, Spark, Google Cloud etc.)
- Proficiency in machine learning and deep learning languages and platforms (Python, R, TensorFlow, Keras, PyTorch, MXNet etc.)
- Experience in deploying machine learning algorithms and advanced modelling solutions
- Experience in developing advanced analytics and ML infrastructure and system
- Self-starter and self-motivated with the proven ability to deliver results in a fast-paced, high-energy environment
- Strong communication skills and the ability to explain complex analysis and algorithms to non-technical audience
- Works effectively cross functional teams to build trusted partnership
- Working experience in digital media and entertainment industry preferred
- Experience with Agile methodologies preferred