Business Analyst

• Bring in industry best practices around creating and maintaining robust data pipelines for complex data projects with/without AI component
  • programmatically ingesting data from several static and real-time sources (incl. web scraping)
  • rendering results through dynamic interfaces incl. web / mobile / dashboard with the ability to log usage and granular user feedbacks
  • performance tuning and optimal implementation of complex Python scripts (using SPARK), SQL (using stored procedures, HIVE), and NoSQL queries in a production environment

• Industrialize ML / DL solutions and deploy and manage production services; proactively handle data issues arising on live apps
• Perform ETL on large and complex datasets for AI applications - work closely with data scientists on performance optimization of large-scale ML/DL model training
• Build data tools to facilitate fast data cleaning and statistical analysis
• Ensure data architecture is secure and compliant
• Resolve issues escalated from Business and Functional areas on data quality, accuracy, and availability
• Work closely with APAC CDO and coordinate with a fully decentralized team across different locations in APAC and global HQ (Paris).

•  Expert in structured and unstructured data in traditional and Big data environments – Oracle / SQLserver, MongoDB, Hive / Pig, BigQuery, and Spark
• Have excellent knowledge of Python programming both in traditional and distributed models (PySpark)
• Expert in shell scripting and writing schedulers
• Hands-on experience with Cloud - deploying complex data solutions in hybrid cloud / on-premise environment both for data extraction/storage and computation
• Hands-on experience in deploying production apps using large volumes of data with state-of-the-art technologies like Dockers, Kubernetes, and Kafka
• Strong knowledge of data security best practices
• 5+ years experience in a data engineering role
• Science / Engineering graduate from a Tier-1 university in the country
• And most importantly, you must be a passionate coder who really cares about building apps that can help people do things better, smarter, and faster even when they sleep

• Partnering with internal business owners (product, marketing, edit, etc.) to understand needs and develop custom analysis to optimize for user engagement and retention
• Good understanding of the underlying business and workings of cross functional teams for successful execution
• Design and develop analyses based on business requirement needs and challenges.
• Leveraging statistical analysis on consumer research and data mining projects, including segmentation, clustering, factor analysis, multivariate regression, predictive modeling, etc.
• Providing statistical analysis on custom research projects and consult on A/B testing and other statistical analysis as needed. Other reports and custom analysis as required.
• Identify and use appropriate investigative and analytical technologies to interpret and verify results.
• Apply and learn a wide variety of tools and languages to achieve results
• Use best practices to develop statistical and/ or machine learning techniques to build models that address business needs.

• 2 - 4 years  of relevant experience in Data science.
• Preferred education: Bachelor's degree in a technical field or equivalent experience.
• Experience in advanced analytics, model building, statistical modeling, optimization, and machine learning algorithms.
• Machine Learning Algorithms: Crystal clear understanding, coding, implementation, error analysis, model tuning knowledge on Linear Regression, Logistic Regression, SVM, shallow Neural Networks, clustering, Decision Trees, Random forest, XGBoost, Recommender Systems, ARIMA and Anomaly Detection. Feature selection, hyper parameters tuning, model selection and error analysis, boosting and ensemble methods.
• Strong with programming languages like Python and data processing using SQL or equivalent and ability to experiment with newer open source tools.
• Experience in normalizing data to ensure it is homogeneous and consistently formatted to enable sorting, query and analysis.
• Experience designing, developing, implementing and maintaining a database and programs to manage data analysis efforts.
• Experience with big data and cloud computing viz. Spark, Hadoop (MapReduce, PIG, HIVE).
• Experience in risk and credit score domains preferred.

1. Create and maintain optimal data pipeline architecture
2. Assemble large, complex data sets that meet business requirements
3. Identifying, designing, and implementing internal process improvements including redesigning infrastructure for greater scalability, optimizing data delivery, and automating manual processes
4. Work with Data, Analytics & Tech team to extract, arrange and analyze data
5. Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS technologies
6. Building analytical tools to utilize the data pipeline, providing actionable insight into key business performance metrics including operational efficiency and customer acquisition
7. Works closely with all business units and engineering teams to develop a strategy for long-term data platform architecture.
8. Working with stakeholders including data, design, product, and executive teams, and assisting them with data-related technical issues
9. Working with stakeholders including the Executive, Product, Data, and Design teams to support their data infrastructure needs while assisting with data-related technical issues.

1. SQL
2. Ruby or Python(Ruby preferred)
3. Apache-Hadoop based analytics
4. Data warehousing
5. Data architecture
6. Schema design
7. ML

1.  Prior experience of 2 to 5 years as a Data Engineer.
2. Ability in managing and communicating data warehouse plans to internal teams.
3. Experience designing, building, and maintaining data processing systems.
4. Ability to perform root cause analysis on external and internal processes and data to identify opportunities for improvement and answer questions.
5. Excellent analytic skills associated with working on unstructured datasets.
6. Ability to build processes that support data transformation, workload management, data structures, dependency, and metadata.

• You'd have to set up your own shop, work with design customers to find generalizable use cases, and build them out.
• Ability to collaborate with cross-functional teams to build and ship new features
• At least 2-5 years of experience
• Predictive Analytics – Machine Learning Algorithms, Logistics & Linear Regression, Decision Tree, Clustering. 
• Exploratory Data Analysis – Data Preparation, Data Exploration, and Data Visualization. 
• Analytics Tools – R, Python, SQL, Power BI, MS Excel.

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