About Entropik Technologies Pvt. Ltd.
SoStronk is a 30 person strong team of gamers, storytellers, engineers, designers and trailblazers who are disrupting gaming and esports at scale. We have built market leading platforms in the esports space for over 5 years and are now positioned for meteoric growth with our latest social gaming platform - IMBR (I am Battle Ready).
Funded by some of the leading strategics in the space - Dream11 (Dream Capital) & Nodwin Gaming (Krafton), IMBR is well on its way to becoming a category creating social gaming platform.
Who you are:
We’re looking for an experienced data scientist who has had success working with experts in cross-functional teams containing Product Managers, Engineers, Designers, and more. A data-driven individual who is just as passionate about data visualization and analytics as they are interested in deconstructing apps, human psychology and gamification.
Our ideal squad-mate is data obsessed, understands the difference between being data informed vs being data blind and is excited by navigating the unknown, collaborating, succeeding and building amazing, industry-leading products: someone who can work iteratively but also knows when it’s time to dream big and shake things up. You are or have
- 3+ years as a Data Scientist: creating measurable impact on features and products. You have a demonstrated track record of scoping and executing complex data projects with high business impact. Startup experience is preferred, ideally in gaming/B2C space.
- Strong programming skills: in Python and SQL and experience with & knowledge of: Cloud platforms such as AWS or Google Cloud; Big data using Hive, Spark, EMR etc
- Full stack data scientist: you are a wizard with the entire pipeline of data analytics, familiarity with analytics platforms such as Amplitude, Branch among others.
- Impact-driven: You understand KPI’s and north star metrics. You get excited by measuring impact of features and taking data-informed decisions with regards to engagement, retention and monetisation.
- Storyteller: You are a storyteller who can convert your data insights into stories with precision and empathy; in doing so get buy-ins from your fellow peers to create impact.
- User-obsessed: You are deeply empathetic, constantly putting yourself in the shoes of the end users, be their psychologist by understanding their internal and external characteristics, be their personal trainer by figuring out what makes them tick so that they achieve their goals.
- Renaissance (wo)man. You’re curious. You’re always learning. You’re as comfortable communicating and empathizing with an end user as you are with a designer or engineer
- Good helicopter. You can alternate between 10,000 foot and 10 foot views easily, and at the right time. Big picture product objectives to microscopic feature alignments all in a day’s work.
- High agency leader. You’re kind, charismatic and humble. Teams want to be in the trenches with you, and to build something great by your side. You are self-driven with regards to constantly analyzing your dashboards to find even the smallest opportunities to optimize for KPIs.
What You’ll Do:
- Create and manage dashboards: Build trust among stakeholders by collaborating with fellow leads and peers on an constantly evolving data pipeline; with company and product milestones in mind.
- Become a domain Leader: Maintain expertise of our domain and market trends, competitor analysis as well as being on the pulse of which mid-core games to support next using platforms such as data.ai (formerly app annie).
- Be a metric driver: Define metrics for everything we should be focusing on building, measure it and drive it. Use data-informed decision making to get buy-in from all your fellow squad members.
- Drive experimentation culture: Figure out ideal A/B tests to increase KPI impact, execute them and continue to evolve experimentation with culture with little to none approval culture.
- Be the glue. Cross-functionally collaborate with growth, design and engineering to drive the product KPIs further. Driving engagement, retention and monetisation strategies as part of a cross-functional team.
- Be the co-pilot. Work closely alongside the founders in driving the product vision, in particular by being the co-pilot of the CPO.
You're also excited by the prospect of rolling up your sleeves to tackle meaningful problems each and every day. You’re a kind, passionate and collaborative problem-solver who seeks and gives candid feedback, and values the chance to make an important impact.
If this sounds like you, you'll fit right in at SoStronk.
- Design, implement and support an analytical data infrastructure, providing ad hoc access to large data sets and computing power.
- Contribute to development of standards and the design and implementation of proactive processes to collect and report data and statistics on assigned systems.
- Research opportunities for data acquisition and new uses for existing data.
- Provide technical development expertise for designing, coding, testing, debugging, documenting and supporting data solutions.
- Experience building data pipelines to connect analytics stacks, client data visualization tools and external data sources.
- Experience with cloud and distributed systems principles
- Experience with Azure/AWS/GCP cloud infrastructure
- Experience with Databricks Clusters and Configuration
- Experience with Python, R, sh/bash and JVM-based languages including Scala and Java.
- Experience with Hadoop family languages including Pig and Hive.
We are in an expansion mode, and thus our team is working on various stages of multiple projects. Thus we require engineers who can come in and remove the roadblocks by identifying time consuming processes and building scalable solutions.
- Candidates need to design and develop recommended systems and consult with the internal team to ensure smooth implementation
- Focus on solving problems and creating value for the team by building solutions that are reliable and scalable
- Develop custom build software on company’s stack
- Improve deployment capacity for customer facing systems using Hadoop, spark, java, python, elastic search
- Hands on experience with Hadoop ecosystem tools like Hive, Sqoop, YARN, HDFS
- Strong scripting experience - python, ruby or bash
- Distributed systems knowledge, preferably ELK or Solr, Kafka, Vertica, Hadoop, RabbitMQ, Storm
- Software and systems solution skills with technologies such as Python, Java, C++, SQL, Hadoop, Elasticsearch,
- Identify solutions and potential snags within engineering
- Have a creative bent in bringing solutions
- Ability to work across the team
- 5+ years of experience
ML Engineer-Analyst/ Senior Analyst
To design and develop machine learning and deep learning systems. Run machine learning tests andexperiments and implementing appropriate ML algorithms. Works cross-functionally with the Data Scientists, Software application developers and business groups for the development of innovative ML models. Use Agile experience to work collaboratively with other Managers/Owners in geographically distributed teams.
- Work with Data Scientists and Business Analysts to frame problems in a business context. Assist all the processes from data collection, cleaning, and preprocessing, to training models and deploying them to production.
- Understand business objectives and developing models that help to achieve them, along with metrics to track their progress.
- Explore and visualize data to gain an understanding of it, then identify differences in data distribution that could affect performance when deploying the model in the real world.
- Define validation strategies, preprocess or feature engineering to be done on a given dataset and data augmentation pipelines.
- Analyze the errors of the model and design strategies to overcome them.
- Collaborate with data engineers to build data and model pipelines, manage the infrastructure and data pipelines needed to bring code to production and demonstrate end-to-end understanding of applications (including, but not limited to, the machine learning algorithms) being created.
Qualifications & Specifications
- Bachelor's degree in Engineering /Computer Science/ Math/ Statistics or equivalent. Master's degree in relevant specification will be first preference
- Experience of machine learning algorithms and libraries
- Understanding of data structures, data modeling and software architecture.
- Deep knowledge of math, probability, statistics and algorithms
- Experience with machine learning platforms such as Microsoft Azure, Google Cloud, IBM Watson, and Amazon
- Big data environment: Hadoop, Spark
- Programming languages: Python, R, PySpark
- Supervised & Unsupervised machine learning: linear regression, logistic regression, k-means
clustering, ensemble models, random forest, svm, gradient boosting
- Sampling data: bagging & boosting, bootstrapping
- Neural networks: ANN, CNN, RNN related topics
- Deep learning: Keras, Tensorflow
- Experience with AWS Sagemaker deployment and agile methodology
Data Platform engineering at Uber is looking for a strong Technical Lead (Level 5a Engineer) who has built high quality platforms and services that can operate at scale. 5a Engineer at Uber exhibits following qualities:
- Demonstrate tech expertise › Demonstrate technical skills to go very deep or broad in solving classes of problems or creating broadly leverageable solutions.
- Execute large scale projects › Define, plan and execute complex and impactful projects. You communicate the vision to peers and stakeholders.
- Collaborate across teams › Domain resource to engineers outside your team and help them leverage the right solutions. Facilitate technical discussions and drive to a consensus.
- Coach engineers › Coach and mentor less experienced engineers and deeply invest in their learning and success. You give and solicit feedback, both positive and negative, to others you work with to help improve the entire team.
- Tech leadership › Lead the effort to define the best practices in your immediate team, and help the broader organization establish better technical or business processes.
What You’ll Do
- Build a scalable, reliable, operable and performant data analytics platform for Uber’s engineers, data scientists, products and operations teams.
- Work alongside the pioneers of big data systems such as Hive, Yarn, Spark, Presto, Kafka, Flink to build out a highly reliable, performant, easy to use software system for Uber’s planet scale of data.
- Become proficient of multi-tenancy, resource isolation, abuse prevention, self-serve debuggability aspects of a high performant, large scale, service while building these capabilities for Uber's engineers and operation folks.
What You’ll Need
- 7+ years experience in building large scale products, data platforms, distributed systems in a high caliber environment.
- Architecture: Identify and solve major architectural problems by going deep in your field or broad across different teams. Extend, improve, or, when needed, build solutions to address architectural gaps or technical debt.
- Software Engineering/Programming: Create frameworks and abstractions that are reliable and reusable. advanced knowledge of at least one programming language, and are happy to learn more. Our core languages are Java, Python, Go, and Scala.
- Data Engineering: Expertise in one of the big data analytics technologies we currently use such as Apache Hadoop (HDFS and YARN), Apache Hive, Impala, Drill, Spark, Tez, Presto, Calcite, Parquet, Arrow etc. Under the hood experience with similar systems such as Vertica, Apache Impala, Drill, Google Borg, Google BigQuery, Amazon EMR, Amazon RedShift, Docker, Kubernetes, Mesos etc.
- Execution & Results: You tackle large technical projects/problems that are not clearly defined. You anticipate roadblocks and have strategies to de-risk timelines. You orchestrate work that spans multiple teams and keep your stakeholders informed.
- A team player: You believe that you can achieve more on a team that the whole is greater than the sum of its parts. You rely on others’ candid feedback for continuous improvement.
- Business acumen: You understand requirements beyond the written word. Whether you’re working on an API used by other developers, an internal tool consumed by our operation teams, or a feature used by millions of customers, your attention to details leads to a delightful user experience.
Octro Inc. is looking for a Data Scientist who will support the product, leadership and marketing teams with insights gained from analyzing multiple sources of data. 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.
They must have strong experience using a variety of data mining/data analysis methods, using a variety of data tools, building and implementing models, using/creating algorithms and creating/running simulations. They must have a proven ability to drive business results with their data-based insights.
They must be comfortable working with a wide range of stakeholders and functional teams. The right candidate will have a passion for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes.
- Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
- Mine and analyze data from multiple 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 modelling to increase and optimize user experiences, revenue generation, ad targeting and other business outcomes.
- Develop various A/B testing frameworks and test model qualities.
- Coordinate with different functional teams to implement models and monitor outcomes.
- Develop processes and tools to monitor and analyze model performance and data accuracy.
- Strong problem solving skills with an emphasis on product development and improvement.
- Advanced knowledge of SQL and its use in data gathering/cleaning.
- Experience using statistical computer languages (R, Python, etc.) to manipulate data and draw insights from large data sets.
- Experience working with and creating data architectures.
- Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
- Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
- Excellent written and verbal communication skills for coordinating across teams.
SQL, Python, Numpy,Pandas,Knowledge of Hive and Data warehousing concept will be a plus point.
- Strong analytical skills with the ability to collect, organise, analyse and interpret trends or patterns in complex data sets and provide reports & visualisations.
- Work with management to prioritise business KPIs and information needs Locate and define new process improvement opportunities.
- Technical expertise with data models, database design and development, data mining and segmentation techniques
- Proven success in a collaborative, team-oriented environment
- Working experience with geospatial data will be a plus.