Work closely with Product Managers to drive product improvements through data driven decisions.
Conduct analysis to determine new project pilot settings, new features, user behaviour, and in-app behaviour.
Present insights and recommendations to leadership using high quality visualizations and concise messaging.
Own the implementation of data collection and tracking, and co-ordinate with engineering and product team.
Create and maintain dashboards for product and business teams.
1+ years’ experience in analytics. Experience as Product analyst will be added advantage.
Technical skills: SQL, Advanced Excel
Good to have: R/Python, Dashboarding experience
Ability to translate structured and unstructured problems into analytical framework
Excellent analytical skills
Good communication & interpersonal skills
Ability to work in a fast-paced start-up environment, learn on the job and get things done.
Client relationship management
Managing Internal stakeholders
3-7 years of experience in digital industry.Must have prior experience in handling clients
Must know SQL (intermediate level) and proficient in Excel
Prior experience in handling digital marketing campaigns .
Must have good experience in campaign data analytics
Prior experience working in Saas based company is a plus
Ability to analyse large volume of data and come up with deep insights
At Porter, we are passionate about improving productivity. We want to help businesses, large and small, optimize their last-mile operations and empower them to unleash the growth of their core functions. Last mile delivery logistics is one of the biggest and fastest growing sectors of the economy with a market cap upwards of 50 billion USD and a growth rate exceeding 15% CAGR.
Porter is the fastest growing leader in this sector with operations in 14 major cities, a fleet size exceeding 1L registered and 50k active driver partners and a customer base with 3.5M being monthly active. Our industry-best technology platform has raised over 50 million USD from investors including Sequoia Capital, Kae Capital, Mahindra group and LGT Aspada.
We are addressing a massive problem and going after a huge market. We’re trying to create a household name in transportation and our ambition is to disrupt all facets of last mile logistics including warehousing and LTL transportation. At Porter, we’re here to do the best work of our lives.
If you want to do the same and love the challenges and opportunities of a fast paced work environment, then we believe Porter is the right place for you.
Company URL: https://porter.in/
- This role requires a person to support & drive business charters & accompanying products by aligning with business & product stakeholders and building & nurturing a team to aid in this. Responsibilities include
Business and product alignment | Analytics scoping and planning
- Understand and align business and product initiatives working with stakeholders.
- Help shape business / product requirements formulation into analytics / data scope.
- Formalize requirements into roadmaps and iterations - accounting for dependencies.
- Drive project execution using effective prioritization and resource allocation.
- Resolve blockers through technical expertise, negotiation, and delegation.
- Strive for completeness of solution through stand-ups and course-correction.
KPIs and metrics
- Drive business-level KPIs
- Ensure all initiatives and product features resonate with and amplify those KPIs.
- Responsible for high-level design and data architecture impacting performance.
- Envision data APIs and set up proper ownership structures.
- Manage a team of 5-8 members and a portfolio of 1-2 business charters.
- Do regular one-on-ones with reportees to ensure resource welfare.
- Periodic assessment and actionable feedback for progress.
- Recruit new members with a view to long-term resource planning through effective collaboration
with the hiring team.
- Formulate SLA benchmarks and set up processes to ensure on-time ad-hoc requests resolution + issues tracking + solving for inefficiencies and effort duplication.
- Establish good code review practices - using this as a nurturing tool.
- Set up communication channels (blog / newsletter) and feedback loops for knowledge sharing and stakeholder management.
- Explore the latest best practices and tools for constant upskilling.
- Analytics : Python / R / SQL + Excel / PPT, Colab notebooks
- Database : PostgreSQL, Amazon Redshift, DynamoDB, Aerospike
- Warehouse : Amazon Redshift
- ETL : Lots of Python + custom-made
- Business Intelligence / Visualization : Metabase + Python/R libraries (location data) + Dash
- Deployment pipeline : Docker, Jenkins, AWS Lambda
- Collaboration : Git, Dropbox Paper
- Analytics experience of minimum 7 years
- Experience managing an Analytics team of at least 4 people end-to-end
- Exposure to consumer facing products (product org experience preferred)
- Strong technical background and ability to contribute to design and review
- Familiarity with our current or a similar analytics stack
- Create and manage cloud resources in AWS
- Data ingestion from different data sources which exposes data using different technologies, such as: RDBMS, REST HTTP API, flat files, Streams, and Time series data based on various proprietary systems. Implement data ingestion and processing with the help of Big Data technologies
- Data processing/transformation using various technologies such as Spark and Cloud Services. You will need to understand your part of business logic and implement it using the language supported by the base data platform
- Develop automated data quality check to make sure right data enters the platform and verifying the results of the calculations
- Develop an infrastructure to collect, transform, combine and publish/distribute customer data.
- Define process improvement opportunities to optimize data collection, insights and displays.
- Ensure data and results are accessible, scalable, efficient, accurate, complete and flexible
- Identify and interpret trends and patterns from complex data sets
- Construct a framework utilizing data visualization tools and techniques to present consolidated analytical and actionable results to relevant stakeholders.
- Key participant in regular Scrum ceremonies with the agile teams
- Proficient at developing queries, writing reports and presenting findings
- Mentor junior members and bring best industry practices
- 5-7+ years’ experience as data engineer in consumer finance or equivalent industry (consumer loans, collections, servicing, optional product, and insurance sales)
- Strong background in math, statistics, computer science, data science or related discipline
- Advanced knowledge one of language: Java, Scala, Python, C#
- Production experience with: HDFS, YARN, Hive, Spark, Kafka, Oozie / Airflow, Amazon Web Services (AWS), Docker / Kubernetes, Snowflake
- Proficient with
- Data mining/programming tools (e.g. SAS, SQL, R, Python)
- Database technologies (e.g. PostgreSQL, Redshift, Snowflake. and Greenplum)
- Data visualization (e.g. Tableau, Looker, MicroStrategy)
- Comfortable learning about and deploying new technologies and tools.
- Organizational skills and the ability to handle multiple projects and priorities simultaneously and meet established deadlines.
- Good written and oral communication skills and ability to present results to non-technical audiences
- Knowledge of business intelligence and analytical tools, technologies and techniques.
- Experience in AWS Glue
- Experience in Apache Parquet
- Proficient in AWS S3 and data lake
- Knowledge of Snowflake
- Understanding of file-based ingestion best practices.
- Scripting language - Python & pyspark
• 2+ years of experience in data engineering & strong understanding of data engineering principles using big data technologies
• Excellent programming skills in Python is mandatory
• Expertise in relational databases (MSSQL/MySQL/Postgres) and expertise in SQL. Exposure to NoSQL such as Cassandra. MongoDB will be a plus.
• Exposure to deploying ETL pipelines such as AirFlow, Docker containers & Lambda functions
• Experience in AWS loud services such as AWS CLI, Glue, Kinesis etc
• Experience using Tableau for data visualization is a plus
• Ability to demonstrate a portfolio of projects (GitHub, papers, etc.) is a plus
• Motivated, can-do attitude and desire to make a change is a must
• Excellent communication skills
- Understanding the business requirements so as to formulate the problems to solve and restrict the slice of data to be explored.
- Collecting data from various sources.
- Performing cleansing, processing, and validation on the data subject to analyze, in order to ensure its quality.
- Exploring and visualizing data.
- Performing statistical analysis and experiments to derive business insights.
- Clearly communicating the findings from the analysis to turn information into something actionable through reports, dashboards, and/or presentations.
- Experience solving problems in the project’s business domain.
- Experience with data integration from multiple sources
- Proficiency in at least one query language, especially SQL.
- Working experience with NoSQL databases, such as MongoDB and Elasticsearch.
- Working experience with popular statistical and machine learning techniques, such as clustering, linear regression, KNN, decision trees, etc.
- Good scripting skills using Python, R or any other relevant language
- Proficiency in at least one data visualization tool, such as Matplotlib, Plotly, D3.js, ggplot, etc.
- Great communication skills.
Job Location: India
We at CondeNast are looking for a data science manager for the content intelligence
workstream primarily, although there might be some overlap with other workstreams. The
position is based out of Chennai and shall report to the head of the data science team, Chennai
1. Ideate new opportunities within the content intelligence workstream where data Science can
be applied to increase user engagement
2. Partner with business and translate business and analytics strategies into multiple short-term
and long-term projects
3. Lead data science teams to build quick prototypes to check feasibility and value to business
and present to business
4. Formulate the business problem into an machine learning/AI problem
5. Review & validate models & help improve the accuracy of model
6. Socialize & present the model insights in a manner that business can understand
7. Lead & own the entire value chain of a project/initiative life cycle - Interface with business,
understand the requirements/specifications, gather data, prepare it, train,validate, test the
model, create business presentations to communicate insights, monitor/track the performance
of the solution and suggest improvements
8. Work closely with ML engineering teams to deploy models to production
9. Work closely with data engineering/services/BI teams to help develop data stores, intuitive
visualizations for the products
10. Setup career paths & learning goals for reportees & mentor them
1. 5+ years of experience in leading Data Science & Advanced analytics projects with a focus on
building recommender systems and 10-12 years of overall experience
2. Experience in leading data science teams to implement recommender systems using content
based, collaborative filtering, embedding techniques
3. Experience in building propensity models, churn prediction, NLP - language models,
embeddings, recommendation engine etc
4. Master’s degree with an emphasis in a quantitative discipline such as statistics, engineering,
economics or mathematics/ Degree programs in data science/ machine learning/ artificial
5. Exceptional Communication Skills - verbal and written
6. Moderate level proficiency in SQL, Python
7. Needs to have demonstrated continuous learning through external certifications, degree
programs in machine learning & artificial intelligence
8. Knowledge of Machine learning algorithms & understanding of how they work
9. Knowledge of Reinforcement Learning
1. Expertise in libraries for data science - pyspark(Databricks), scikit-learn, pandas, numpy,
matplotlib, pytorch/tensorflow/keras etc
2. Working Knowledge of deep learning models
3. Experience in ETL/ data engineering
4. Prior experience in e-commerce, media & publishing domain is a plus
5. Experience in digital advertising is a plus
About Condé Nast
CONDÉ NAST INDIA (DATA)
Over the years, Condé Nast successfully expanded and diversified into digital, TV, and social
platforms - in other words, a staggering amount of user data. Condé Nast made the right move
to invest heavily in understanding this data and formed a whole new Data team entirely
dedicated to data processing, engineering, analytics, and visualization. This team helps drive
engagement, fuel process innovation, further content enrichment, and increase market
revenue. The Data team aimed to create a company culture where data was the common
language and facilitate an environment where insights shared in real-time could improve
The Global Data team operates out of Los Angeles, New York, Chennai, and London. The team
at Condé Nast Chennai works extensively with data to amplify its brands' digital capabilities and
boost online revenue. We are broadly divided into four groups, Data Intelligence, Data
Engineering, Data Science, and Operations (including Product and Marketing Ops, Client
Services) along with Data Strategy and monetization. The teams built capabilities and products
to create data-driven solutions for better audience engagement.
What we look forward to:
We want to welcome bright, new minds into our midst and work together to create diverse
forms of self-expression. At Condé Nast, we encourage the imaginative and celebrate the
extraordinary. We are a media company for the future, with a remarkable past. We are Condé
Nast, and It Starts Here.
● The machine learning team is a self-contained team of 9 people responsible for building models and services that support key workflows for IDfy.
● Our models are gating criteria for these workflows and as such are expected to perform accurately and quickly. We use a mix of conventional and hand-crafted deep learning models.
● The team comes from diverse backgrounds and experiences. We have ex-bankers, startup founders, IIT-ians, and more.
● We work directly with business and product teams to craft solutions for our customers. We know that we are, and function as a platform and not a services company.
● Be working on all aspects of a production machine learning system. You will be acquiring data, training and building models, deploying models, building API services for exposing these models, maintaining them in production, and more.
● Work on performance tuning of models
● From time to time work on support and debugging of these production systems
● Work on researching the latest technology in the areas of our interest and applying it to build newer products and enhancement of the existing platform.
● Building workflows for training and production systems
● Contribute to documentation
● You are an early-career machine learning engineer (or data scientist). Our ideal candidate is
someone with 1-3 years of experience in data science.
● You have a good understanding of Python and Scikit-learn, Tensorflow, or Pytorch. Our systems are built with these tools/language and we expect a strong base in these.
● You are proficient at exploratory analysis and know which model to use in most scenarios
● You should have worked on framing and solving problems with the application of machine learning or deep learning models.
● You have some experience in building and delivering complete or part AI solutions
● You appreciate that the role of the Machine Learning engineer is not only modeling, but also building product solutions and you strive towards this.
● Enthusiasm and drive to learn and assimilate the state of art research. A lot of what we are building will require innovative approaches using newly researched models and applications.
Good to Have
● Knowledge of and experience in computer vision. While a large part of our work revolves around computer
vision, we believe this is something you can learn on the job.
● We build our own services, hence we would want you to have some knowledge of writing APIs.
● Our stack also includes languages like Ruby, Go, and Elixir. We would love it if you know any of these or take an interest in functional programming.
● Knowledge of and experience in ML Ops and tooling would be a welcome addition. We use Docker and Kubernetes for deploying our services.
We are seeking Machine Learning Engineers to join our engineering team, with C/C++ background to work on TensorRT, CuDNN, PyTorch C++ API, and good knowledge of handling databases. The position will involve taking these skills and applying them to real-world problems.
- Build computer vision algorithms on resource constrained devices
- Work on cutting edge problems in Deep Learning for Internal AI Accelerator SW Stack
- Develop & integrate functional and performance models of accelerators
- Analyzing the accuracy of Neural Network on Functional models and correlate with HW implementation
- Be part of discussions in defining the next gen HW accelerators
- Research on various numerics related to Machine Learning, optimizing it based on design and performance constraints
- Experience in embedded Computer Vision (Open CV), SIMD, and parallel computing, with a deep understanding of CV algorithms and multimedia image formats
- Fluent in working with Python
- Fluent in C and C++ as well as experience in CUDA
- Efficient in SW development in Linux, with a deep understanding of operating system e.g. Linux,
- Good knowledge in SoCs e.g. Tegra, with efficient use of Software development tools like debuggers
- Excellent written and verbal interpersonal skills and an eye for detail
- Good organization skills, with a logical approach to problem-solving, time management and ability to prioritize
Ways to stand out from the crowd:
- Experience with visual geometry and deep learning in a shipping product context
- Worked on real-time Image Processing and/or computer vision systems
- Software development on embedded platforms or large scale cloud services
- Experience with GPGPU programming (CUDA and OpenGL)
- Worked on atleast one mainstream deep learning frameworks, including TensorFlow, Caffe(2), MXNet, PyTorch
- Be the analytical expert in Kaleidofin, managing ambiguous problems by using data to execute sophisticated quantitative modeling and deliver actionable insights.
- Develop comprehensive skills including project management, business judgment, analytical problem solving and technical depth.
- Become an expert on data and trends, both internal and external to Kaleidofin.
- Communicate key state of the business metrics and develop dashboards to enable teams to understand business metrics independently.
- Collaborate with stakeholders across teams to drive data analysis for key business questions, communicate insights and drive the planning process with company executives.
- Automate scheduling and distribution of reports and support auditing and value realization.
- Partner with enterprise architects to define and ensure proposed.
- Business Intelligence solutions adhere to an enterprise reference architecture.
- Design robust data-centric solutions and architecture that incorporates technology and strong BI solutions to scale up and eliminate repetitive tasks.
- Experience leading development efforts through all phases of SDLC.
- 2+ years "hands-on" experience designing Analytics and Business Intelligence solutions.
- Experience with Quicksight, PowerBI, Tableau and Qlik is a plus.
- Hands on experience in SQL, data management, and scripting (preferably Python).
- Strong data visualisation design skills, data modeling and inference skills.
- Hands-on and experience in managing small teams.
- Financial services experience preferred, but not mandatory.
- Strong knowledge of architectural principles, tools, frameworks, and best practices.
- Excellent communication and presentation skills to communicate and collaborate with all levels of the organisation.
- Preferred candidates with less than 30 days notice period.
High Level Scope of Work :
- Work with AI / Analytics team to priorities MACHINE LEARNING Identified USE CASES for Development and Rollout
- Meet and understand current retail / Marketing Requirements and how AI/ML solution will address and automate the decision process.
- Develop AI/ML Programs using DATAIKU Solution & Python or open source tech with focus to deliver high Quality and accurate ML prediction Model
- Gather additional and external data sources to support the AI/ML Model as desired .
- Support the ML Model and FINE TUNEit to ensure high accuracy all the time.
- Example of use cases (Customer Segmentation , Product Recommendation, Price Optimization, Retail Customer Personalization Offers, Next Best Location for Business Est, CCTV Computer Vision, NLP and Voice Recognition Solutions)
Required technology expertise :
- Deep Knowledge & Understanding on MACHINE LEARNING ALGORITHMS (Supervised / Unsupervised Learning / Deep Learning Models)
- Hands on EXP for at least 5+ years with PYTHON and R STATISTICS PROGRAMMING Languages
- Strong Database Development knowledge using SQL and PL/SQL
- Must have EXP using Commercial Data Science Solution particularly DATAIKU and (Altryx, SAS, Azure ML, Google ML, Oracle ML is a plus)
- Strong hands on EXP with BIG DATA Solution Architecture and Optimization for AI/ML Workload.
- Data Analytics and BI Tools Hand on EXP particularly (Oracle OBIEE and Power BI)
- Have implemented and Developed at least 3 successful AI/ML Projects with tangible Business Outcomes In retail Focused Industry
- Have at least 5+ Years EXP in Retail Industry and Customer Focus Business.
- Ability to communicate with Business Owner & stakeholders to understand their current issues and provide MACHINE LEARNING Solution accordingly.
- Bachelor Degree or Master Degree in Data Science, Artificial Intelligent, Computer Science
- Certified as DATA SCIENTIST or MACHINE LEARNING Expert.