Company Overview Akridata is a US based early stage startup working in the area of providing data processing and data management solutions for certain edge to data center pipelines related to AI workloads catering to use cases generating data in the order of 100TB per day. We are a VC funded startup incorporated in May 2018 with all SW engineering done from the Bangalore center thus providing ample opportunities for ‘from-scratch’ design and development. Role We are in the process of setting up a “data science and algorithms” team and this role is for a lead engineer who will form the team and lead all development activities for this team. This team will develop high performance algorithms around the areas of data summarization and importance scoring on data. If you are excited with the idea of developing a data-science toolkit Vs using an existing toolkit, then this role would be an ideal match. What we are looking for Master’s degree with a background in statistics and computer science. Good foundation on theory around advanced linear algebra. Hands-on programming experience with Python in area of data science 4+ years of experience working with data science activities involving building models for analysing large amounts of data. Experience with publishing academic papers and/or implementing prototypes based on ongoing research ideas. Good to have Experience with developing high performance algorithms considering various system aspects like memory consumption, CPU utilization, synchronization overheads, communication overheads etc. Understanding of GPU architecture and experience implementing algorithms on GPUs. Experience leading a team of 2-3 data science engineers.
Data Scientist Job Profile: We are looking for a Data Scientist who will support our product, sales, leadership and marketing teams with insights gained from analyzing company 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. Responsibilities for Data Scientist: Data 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. Coordinate with different functional teams to implement models and monitor outcomes. Develop processes and tools to monitor and analyze model performance and data accuracy. Qualifications for Data Scientist Masters in Statistics , Econometric Statistics . Strong problem-solving skills with an emphasis on product development. Experience using statistical computer languages (R, Python, SQL, etc.) to manipulate data and draw insights from large data sets and 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. A drive to learn and master new technologies and techniques. We’re looking for someone with 3-5 years of experience manipulating data sets and building statistical models, has a master’s or PHD in Statistics, Mathematics, Computer Science or another quantitative field, and is familiar with the following software/tools: Coding knowledge and experience with several language C++, python, R. Experience querying databases and using statistical computer languages: R, Python, SQL, etc. Experience visualizing/presenting data for stakeholders using: BI tools. Job Perks Free lunch Monthly team lunch,outing.
Lead Data Scientist in a Fantasy sports company You will be working for India's fastest growing fantasy sports app, to analyze and enhance user behavior, pre-empt and prevent user drop offs, and provide strategic guidance on user behavior to Product and Retention teams. Responsibilities: 1. Analyze millions of transactions to find patterns in user spends, segment them and improve conversions 2. Design experiments in consultation with Product team, test hypotheses, build models, drive control groups and scale 3. Conduct advanced statistical analysis to provide actionable insights, identify trends, and measure performance for re-engagement activities 4. Work with various stakeholders to identify their processes, and provide feedback to analyze their efficacy 5. Provide data based recommendations for new app features and modifications of existing flows and paradigms 6. Designing and developing new ML, analytical or AI algorithms for increasing 7. Lead the ownership of data and insights, and take a lead in formulating strategic initiatives Qualifications: 1. 3-5 experience working in Data Science department of a B2C company or an Analytics firm or an Analytics Consulting firm 2. Understanding of statistical modeling (Regression, Clustering, Decision trees), machine learning, algorithms, data mining concepts, and a track record of solving problems with these methods 3. Experience with Deep Learning, SVM, k-nearest neighbors, Random Forests, Ensemble Methods, Logistic Regression, Probability Theory, Bayesian/Markov networks etc. 4. Demonstrated programming skills in relevant languages, including R, Python, SQL 5. Demonstrated analytical ability, knack in figuring out patterns in raw data and good problem-solving skills 6. Great people skills, ability to work across teams, get stakeholders on board in implementing changes 7. Strong interest in Mathematics, Probability Theory, Statistics, Machine Learning and ability to apply math in real world applications
About us: Quantiphi is a category defining Data Science and Machine Learning Software and Services Company focused on helping organizations translate the big promise of Big Data & Machine Learning technologies into quantifiable business impact. We were founded on the belief that machine learning and artificial intelligence are transformative technologies that will create the next quantum gain in customer experience and unit economics of businesses. Quantiphi helps clients find and capture hidden value from data through a unique blend of business acumen, big-data, machine learning and intuitive information design. AthenasOwl (AO) is our “AI for Media” solution that helps content creators and broadcasters to create and curate smarter content. We launched the product in 2017 as an AI-powered suite meant for the media and entertainment industry. Clients use AthenaOwl's context adapted technology for redesigning content, taking better targeting decisions, automating hours of post-production work and monetizing massive content libraries. Please Find Attached fact sheet for your reference. For more details visit: www.quantiphi.com ; www.athenasowl.tv Job Description: -Developing high-level solution architecture related to different use-cases in the media industry -Leveraging both structured and unstructured data from external sources and our proprietary AI/ML models to build solutions and workflows that can be used to give data driven insights. -Develop sophisticated yet easy to digest interpretations and communicate insights to clients that lead to quantifiable business impact. -Building deep relationship with clients by understanding their stated but more importantly, latent needs. -Working closely with the client-side delivery managers to ensure a seamless communication and delivery cadence. Essential Skills and Qualifications: -Hands-on experience with statistical tools and techniques in Python -Great analytical skills, with expertise in analytical toolkits such as Logistic Regression, Cluster Analysis, Factor Analysis, Multivariate Regression, Statistical modelling, predictive analysis. -Advanced knowledge of supervised and unsupervised machine learning algorithms like Random Forest, Boosting, SVM, Neural Networks, Collaborative filtering etc. -Ability to think creatively and work well both as part of a team and as an individual contributor -Critical eye for the quality of data and strong desire to get it right -Strong communication skills. -Should be able to read a paper and quickly implement ideas from scratch. -A pleasantly forceful personality and charismatic communication style.
How often have you read job descriptions and gone ‘I have read this before’ or ‘the real job description will come out during the interviews, so why bother reading this’. In other instances when job descriptions are actually well-written, ie not just copied and pasted from somewhere and try doing justice to what you’d be doing at the job, 2-4 months of a typical interview cycle make those descriptions obsolete by the time you actually start at the job. Also not unsurprising then: just like you ignore or skim through job descriptions, most recruiters do the same with your resumes – look for specific keywords and leave all the assessment for during the interview itself. Even worse: the human recruiter in some cases is being replaced by an algorithm to automate screening. You, therefore, will try to put as many keywords in your resume to ensure you get that interview call. Nobody is being ingenuine in this process but the very process is fundamentally broken. And that is exactly what we want to solve: create an effective ‘matching of work to the worker’ that is an accurate and real-time reflection of both ends, thus increasing the actual engagement with the work itself. Responsibilities In this role, you’ll build and implement novel Machine Learning and Deep Learning systems on our platform as well as help build the infrastructure to train and deploy them. Specifically, you will: - Design and implement the infrastructure required to train models at scale. - Work with the data team’s infrastructure to build real-time and offline feature databases. - Work with the data team to create the infrastructure to build and maintain the datasets from which models are created - Build the model serving systems with which we can deploy our models to production - As we grow, scale the ML system to be able to support more use cases and ML model types. Requirements - 1+ years of experience building production-ready ML models and systems. - 3+ years of building distributed systems and/or scalable backend systems and the ability to maintain such systems in production. - Strong software engineering fundamentals - understanding of data structures and algorithms, O-notation, ability to maintain a test suite and write clear maintainable code. - Familiarity with the majority of the following tools: Tensorflow, Numpy, Scipy, SparkML, pandas, scikit-learn. - Demonstrated leadership and self-direction and willingness to both teach others and learn new techniques. - Experience with big data processing and storage systems: Hadoop, Spark, Hbase, Cassandra etc. - Strong programming skills in Python. Intermediate to Advanced knowledge of SQL and ability to wrangle data from many disparate data sources - Technologies we use: MySQL, Python, AWS, Snowflake, R, and Looker, among many others.
We're building a quantitative hedge fund seeking developers to work with our traders in building trading systems. The ideal candidate will have a strong technical background in Python and/or C++ having experience working on some machine learning/deep learning/statistics project WHAT YOU WILL DO: - Build In-house robust systems - Evaluate new data sets for potential alpha generation WHO YOU ARE: - You have a background in Statistics and Computer Science - team person with a passion for solving hard problems in novel ways - Technically literate and able (and willing) to work without the support of a large quant/bank infrastructure - Comfortable working independently, crafting solutions to projects and problems first hand - Comfortable working in high growth, constantly-changing environment Conditions * Start date: May/June 2019 * Initial 1 year contract, with a 3 months probation period