More about us : bit.ly/workatjarapp
Jar is seeking a talented Senior Product Analyst to join our Team. If you are intellectually curious, if you eat/sleep/drink data and are committed to translating data to insights & insights to actionable work items, want new challenges daily and impact the lives of hundreds of thousands of users, this is the role for you!
What You Will Do
- Deliver insight and analysis using statistical tools, data visualization, and business use cases with the Product and Business teams
- Understanding of tools like product analytics and engagement platforms like Clevertap, Amplitude, Apxor etc
- Conduct analysis to determine new project pilot settings, new features, user behaviour, and in-app behaviour
- Build & maintain dashboards for tracking business performance and product adoption
- Assist Product Managers and Business teams in creating data-backed decisions
- Collaborate with Consumer Platform's Product and Business teams in identifying new avenues for growth and opportunities, and back their product delivery with experimentation
- Build first cut Machine Learning models based on product requirements
- Automate data extraction by creating de-normalized tables
What You Will Need
- At least 2+ years of work experience dealing with product analytics, data, and statistics
- Expertise in SQL with experience using data visualization and dashboarding tools (e.g. Tableau, Metabase, Google Data Studio, Clevertap, Python)
- Experience in Machine Learning technologies (i.e. forecasting, clustering, statistical significance test, predictive modeling, and text mining)
- Experience in delivering products as end-to-end data solutions (from data pipelining to analysis, presenting, and scalable adaption)
- A strong business sense with the ability to transform ambiguous business and product issues into well-scoped, impactful analysis
- Strong ability to design and conduct simple experiments
- A goal-oriented, critical-thinking mindset with the ability to work equally well within a team and independently with minimal supervision
Hey! We are building this exciting product in the space of micro wealth management for GenZ and Millennials.
400+ Million people are waiting to be financially literate, learn to save and make smart investments one step at a time. That's what India is right now and we are doing everything to ensure that it happens. A financial literate young population is potent enough to change the world.
We are here to help Indians to rediscover savings in the times of instant gratification, inflation and never ending need of assimilation into western philosophy of consumerism.
You ask how we are going to do it? We are building a micro wealth management platform with small steps at a time, starting with micro savings, financial literacy and then to the glory of micro investments.
We are backed by serial entrepreneurs and marquee operators 💰
- Building & delivering analytics mandates for our clients across different problem definitions in different B2C verticals
- Deliver analytical solutions for leveraging deep business understanding and analytical expertise
- Lead client engagements and assignments to ensure successful and timely delivery of output with high quality and in accordance with client's needs and expectations
- Understand the business problem and build the analytical solution framework leveraging advanced Clootrack analytics algorithms as well as visualization platforms as needed. Generate insights and present findings to the client that meet business requirements
- Manage medium-sized teams, contribute to performance appraisals and develop career progression metrics.
- The role also encompasses design & review of the solution, scaling and institutionalizing analytics for our clients, program management, and meeting our engagement goals
- Lead by example, mentor the team & drive rigorous project management to meet client goals.
- Engineering from a reputed institute.
- Good to have: MBA from a reputed institute
Qualifications & Experience
- Proven track record to deliver Analytics engagements with at least 4 years of working experience
- Ability to independently manage analytics engagements from start to finish, delivering actionable insight within established timelines and budget. Experience working in a consultative capacity (internal or external) is a strong plus
- Knowledge of advanced analytics including but not limited to Regression, GLMs, survival modeling, forecasting, machine learning, decision trees etc. using statistical or analytic tools like SAS, R etc.
- Knowledge of advanced visualization platforms like Qlikview, Tableau, Spotfire etc.
- Demonstrated ability in driving business impact through the application of data science and analytical techniques. Understanding and leveraging the connection between data structures, analytical methods, and business applications.
- Strong analytical thinking skills. Ability to creatively solve business problems, innovating new approaches where required.
- Good verbal and written communication skills & must have excellent project management skills and have experience managing multiple work streams and projects at one time
- Building and, when necessary, rebuilding -- and leading high-performance teams. Proven track record of identifying and developing analytical talent and leading a team of quantitative personnel.
- Must have curiosity and love to ask the question 'why'
- The person should be open to travel to client locations across multiple geographies for shorter durations depending on the engagement
- Good to have: Analytics: SAS/R / Python; R, Visualization tools – Qlikview, Tableau, Spotfire etc.
Mid / Senior Big Data Engineer
Role: Big Data EngineerNumber of open positions: 5Location: PuneAt Clairvoyant, we're building a thriving big data practice to help enterprises enable and accelerate the adoption of Big data and cloud services. In the big data space, we lead and serve as innovators, troubleshooters, and enablers. Big data practice at Clairvoyant, focuses on solving our customer's business problems by delivering products designed with best in class engineering practices and a commitment to keep the total cost of ownership to a minimum.
- 4-10 years of experience in software development.
- At least 2 years of relevant work experience on large scale Data applications.
- Strong coding experience in Java is mandatory
- Good aptitude, strong problem solving abilities, and analytical skills, ability to take ownership as appropriate
- Should be able to do coding, debugging, performance tuning and deploying the apps to Prod.
- Should have good working experience on
- o Hadoop ecosystem (HDFS, Hive, Yarn, File formats like Avro/Parquet)
- o Kafka
- o J2EE Frameworks (Spring/Hibernate/REST)
- o Spark Streaming or any other streaming technology.
- Strong coding experience in Java is mandatory
- Ability to work on the sprint stories to completion along with Unit test case coverage.
- Experience working in Agile Methodology
- Excellent communication and coordination skills
- Knowledgeable (and preferred hands on) - UNIX environments, different continuous integration tools.
- Must be able to integrate quickly into the team and work independently towards team goals
- Take the complete responsibility of the sprint stories' execution
- Be accountable for the delivery of the tasks in the defined timelines with good quality.
- Follow the processes for project execution and delivery.
- Follow agile methodology
- Work with the team lead closely and contribute to the smooth delivery of the project.
- Understand/define the architecture and discuss the pros-cons of the same with the team
- Involve in the brainstorming sessions and suggest improvements in the architecture/design.
- Work with other team leads to get the architecture/design reviewed.
- Work with the clients and counter-parts (in US) of the project.
- Keep all the stakeholders updated about the project/task status/risks/issues if there are any.
Experience: 4 to 9 years
Keywords: java, scala, spark, software development, hadoop, hive
- Modeling complex problems, discovering insights, and identifying opportunities through the use of statistical, algorithmic, mining, and visualization techniques
- Experience working with business understanding the requirement, creating the problem statement, and building scalable and dependable Analytical solutions
- Must have hands-on and strong experience in Python
- Broad knowledge of fundamentals and state-of-the-art in NLP and machine learning
- Strong analytical & algorithm development skills
- Deep knowledge of techniques such as Linear Regression, gradient descent, Logistic Regression, Forecasting, Cluster analysis, Decision trees, Linear Optimization, Text Mining, etc
- Ability to collaborate across teams and strong interpersonal skills
- Sound theoretical knowledge in ML algorithm and their application
- Hands-on experience in statistical modeling tools such as R, Python, and SQL
- Hands-on experience in Machine learning/data science
- Strong knowledge of statistics
- Experience in advanced analytics / Statistical techniques – Regression, Decision trees, Ensemble machine learning algorithms, etc
- Experience in Natural Language Processing & Deep Learning techniques
- Pandas, NLTK, Scikit-learn, SpaCy, Tensorflow
Remote Work, US shift
General Scope and Summary
The Data and Analytics Team sits in the Digital and Enterprise Capabilities Group and is responsible for driving the strategy, implementation and delivery of Data,
Analytics and Automation capabilities across Enterprise.
This global team will deliver “Next-Gen Value” by establishing core Data and Analytics capabilities needed to effectively manage and exploit Data as an Enterprise Asset. Data Platform Operations will be responsible for implementing and supporting Enterprise Data Operations tools and capabilities which will enable teams
to answer strategic and business questions through data .
Roles and Responsibilities
● Manage overall data operations ensuring adherence to data quality metrics by establishing standard operating procedures and best practices/playbooks.
● Champion the advocacy and adoption of enterprise data assets for analytics and analytics through optimal operating models.
● Provide day-to-day ownership and project management data operations activities including data quality/data management support cases and other ad-hoc requests.
● Create standards, frameworks for CI/CD pipelines and DevOps.
● Collaborative cross-functionally to develop and implement data operations policies balancing centralized control and standardization with decentralized speed and flexibility.
● Identify areas for improvement. Create procedures, teams, and policies to support near real-time clean data, where applicable, or in a batch and close process, where applicable.
● Improve processes by tactically focusing on business outcomes. Drive prioritization based on business needs and strategy.
● Lead and control workflow operations by driving critical issues and discussions with partners to identify and implement improvements.
● Responsible for defining, measuring, monitoring, and reporting of key SLA metrics to support its vision.
Experience, Education and Specialized Knowledge and Skills
Must thrive working in a fast-paced, innovative environment while remaining flexible, proactive, resourceful, and efficient. Strong interpersonal skills, ability to understand
stakeholder pain points, ability to analyze complex issues to develop relevant and realistic solutions and recommendations. Demonstrated ability to translate strategy into action; excellent technical skills and an ability to communicate complex issues in a simple way and to orchestrate solutions to resolve issues and mitigate risks.
Work Location : Chennai
Experience Level : 5+yrs
Package : Upto 18 LPA
Notice Period : Immediate Joiners
It's a full-time opportunity with our client.
Mandatory Skills:Machine Learning,Python,Tableau & SQL
--2+ years of industry experience in predictive modeling, data science, and Analysis.
--Experience with ML models including but not limited to Regression, Random Forests, XGBoost.
--Experience in an ML engineer or data scientist role building and deploying ML models or hands on experience developing deep learning models.
--Experience writing code in Python and SQL with documentation for reproducibility.
--Strong Proficiency in Tableau.
--Experience handling big datasets, diving into data to discover hidden patterns, using data visualization tools, writing SQL.
--Experience writing and speaking about technical concepts to business, technical, and lay audiences and giving data-driven presentations.
--AWS Sagemaker experience is a plus not required.
- 6+ years of recent hands-on Java development
- Developing data pipelines in AWS or Google Cloud
- Great understanding of designing for performance, scalability, and reliability of data intensive application
- Hadoop MapReduce, Spark, Pig. Understanding of database fundamentals and advanced SQL knowledge.
- In-depth understanding of object oriented programming concepts and design patterns
- Ability to communicate clearly to technical and non-technical audiences, verbally and in writing
- Understanding of full software development life cycle, agile development and continuous integration
- Experience in Agile methodologies including Scrum and Kanban
- Product Analytics: This is the first and most obvious role of the Product Analyst. At this capacity, the Product Analyst is responsible for the development and delivery of tangible consumer benefits through the product or service of the business.
- In addition, in this capacity, the Product Analyst is also responsible for measuring and monitoring the product or service’s performance as well as presenting product-related consumer, market, and competitive intelligence.
- Product Strategy: As a member of the Product team, the Product Analyst is responsible for the development and proposal of product strategies.
- Product Management Operations: The Product Analyst also has the obligation to respond in a timely manner to all requests and inquiries for product information or changes. He also performs the initial product analysis in order to assess the need for any requested changes as well as their potential impact.
- At this capacity, the Product Analyst also undertakes financial modeling on the products or services of the business as well as of the target markets in order to bring about an understanding of the relations between the product and the target market. This information is presented to the Marketing Manager and other stakeholders, when necessary.
- Additionally, the Product Analyst produces reports and makes recommendations to the Product Manager and Product Marketing Manager to be used as guidance in decision-making pertaining to the business’s new as well as existent products.
- Initiative: In this capacity, the Product Analyst ensures that there is a good flow of communication between the Product team and other teams. The Product Analyst ensures this by actively participating in team meetings and keeping everyone up to date.
- Pricing and Development: The Product Analyst has the responsibility to monitor the market, competitor activities, as well as any price movements and make recommendations that will be used in key decision making. In this function, the Product Analyst will normally liaise with other departments such as the credit/risk in the business in order to enhance and increase the efficiency of effecting price changes in accordance with market shifts.
- Customer/Market Intelligence: The Product Analyst has the obligation to drive consumer intelligence through the development of external and internal data sources that improve the business’s understanding of the product’s market, competitor activities, and consumer activities.
- In the performance of this role, the Product Analyst develops or adopts research tools, sources, and methods that further support and contribute to the business’s product.
About MX Player (https://play.google.com/store/apps/details?id=com.mxtech.videoplayer.ad&hl=en_IN">Playstore Link)
MX Player is the world’s #1 entertainment superapp offering 100,000+ hours of premium OTT (over the top) content spanning acclaimed MX Originals, Web Shows, TV (Live & OnDemand), movies, music videos and hyper-casual games, music streaming, short form video and more. With more than 1 billion installs worldwide – MX Player is present on 1 out of every 2 smartphones, making it the largest entertainment app/platform in the world.
Position : Product Analyst / Business Analyst - Ad Tech
- Driving the collection of new data that would help build the next generation of algorithms (E.g. audience segmentation, contextual targeting)
- Understanding user behavior and performing root-cause analysis of changes in data trends to identify corrections or propose desirable enhancements in product & across different verticals
- Excellent problem solving skills and the ability to make sound judgments based on trade-offs for different solutions to complex problem constraints
- Defining and monitoring KPIs for product/content/business performance and identifying ways to improve them
- Should be a strong advocate of data driven approach and drive analytics decisions by doing user testing, data analysis, and A/B testing
- Help in defining the analytics roadmap for the product
- Prior knowledge and experience in ad tech industry or other advertising platforms will be preferred
- Knowledge of Google DFP (prefered)
- R/Python (preferred)
- Any BI Tool such as tableau, sisense (preferred)
- Go getter attitude
- Ability to thrive in a fast paced dynamic environment
- Self - Starter
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
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