> Selecting features, building and optimizing classifiers using machine
> learning techniques
> Data mining using state-of-the-art methods
> Extending company’s data with third party sources of information when
> Enhancing data collection procedures to include information that is
> relevant for building analytic systems
> Processing, cleansing, and verifying the integrity of data used for
> Doing ad-hoc analysis and presenting results in a clear manner
> Creating automated anomaly detection systems and constant tracking of
> its performance
> Hands-on experience of analysis tools like R, Advance Python
> Must Have Knowledge of statistical techniques and machine learning
> Artificial Intelligence
> Understanding of Text analysis- Natural Language processing (NLP)
> Knowledge on Google Cloud Platform
> Advanced Excel, PowerPoint skills
> Advanced communication (written and oral) and strong interpersonal
> Ability to work cross-culturally
> Good to have Deep Learning
> VBA and visualization tools like Tableau, PowerBI, Qliksense, Qlikview
> will be an added advantage
Subodh PopalwarSoftware Engineer, Memorres
About India Bison
● Knowledge of Excel,SQL and writing code in python.
● Experience with Reporting and Business Intelligence tools like Tableau, Metabase.
● Exposure with distributed analytics processing technologies is desired (e.g. Hive, Spark).
● Experience with Clevertap, Mixpanel, Amplitude, etc.
● Excellent communication skills.
● Background in market research and project management.
● Attention to detail.
● Problem-solving aptitude.
- Data science model review, run the code refactoring and optimization, containerization, deployment, versioning, and monitoring of its quality.
- Design and implement cloud solutions, build MLOps on the cloud (preferably AWS)
- Work with workflow orchestration tools like Kubeflow, Airflow, Argo, or similar tools
- Data science models testing, validation, and test automation.
- Communicate with a team of data scientists, data engineers, and architects, and document the processes.
- 4+ years of experience in MLOps
- Rich hands-on experience in writing object-oriented code using python
- Min 3 years of MLOps experience (Including model versioning, model and data lineage, monitoring, model hosting and deployment, scalability, orchestration, continuous learning, and Automated pipelines)
- Understanding of Data Structures, Data Systems, and software architecture
- Experience in using MLOps frameworks like Kubeflow, MLFlow, and Airflow Pipelines for building, deploying, and managing multi-step ML workflows based on Docker containers and Kubernetes.
- Exposure to deep learning approaches and modeling frameworks (PyTorch, Tensorflow, Keras, etc. )
We are looking for a Quantitative Developer who is passionate about financial markets and wants to join a scale-up with an excellent track record and growth potential in an innovative and fast-growing industry.
As a Quantitative Developer, you will be working on the infrastructure of our platform,as part of a very ambitious team.
At QCAlpha you have the freedom to choose the path that leads to the solution and get a lot of responsibility.
• Design, develop, test, and deploy elegant software solutions for automated trading systems
• Building high-performance, bullet-proof components for both live trading and simulation
• Responsible for technology infrastructure systems development, which includes connectivity, maintenance, and internal automation processes
• Achieving trading system robustness through automated reconciliation and system-wide alerts
• Bachelor’s degree or higher in computer science or other quantitative discipline
• Strong fundamental knowledge of OOP programming, algorithms, data structures and design patterns.
• Familiar with the following technology stacks: Linux shell, Python and its ecosystem, NumPy, Pandas, SQL, Redis, Docker or similar system
• Experience in python frameworks such as Django or Flask.
• Solid understanding of git, ci/cd.
• Excellent design, debugging and problem-solving skills.
• Proven versatility and ability to pick up new technologies and learn systems quickly.
• Trading Execution development and support experience is a plus.
Building out and manage a young data science vertical within the organization
Provide technical leadership in the areas of machine learning, analytics, and data sciences
Work with the team and create a roadmap to solve the company’s requirements by solving data-mining, analytics, and ML problems by Identifying business problems that could be solved using Data Science and scoping it out end to end.
Solve business problems by applying advanced Machine Learning algorithms and complex statistical models on large volumes of data.
Develop heuristics, algorithms, and models to deanonymize entities on public blockchains
Data Mining - Extend the organization’s proprietary dataset by introducing new data collection methods and by identifying new data sources.
Keep track of the latest trends in cryptocurrency usage on open-web and dark-web and develop counter-measures to defeat concealment techniques used by criminal actors.
Develop in-house algorithms to generate risk scores for blockchain transactions.
Work with data engineers to implement the results of your work.
Assemble large, complex data sets that meet functional / non-functional business requirements.
Build, scale and deploy holistic data science products after successful prototyping.
Clearly articulate and present recommendations to business partners, and influence future plans based on insights.
>8+ years of relevant experience as a Data Scientist or Analyst. A few years of work experience solving NLP problems or other ML problems is a plus
Must have previously managed a team of at least 5 data scientists or analysts or demonstrate that they have prior experience in scaling a data science function from the ground
Good understanding of python, bash scripting, and basic cloud platform skills (on GCP or AWS)
Excellent communication skills and analytical skills
What you’ll get
Work closely with the Founders in helping grow the organization to the next level alongside some of the best and brightest talents around you
An excellent culture, we encourage collaboration, growth, and learning amongst the team
Competitive salary and equity
An autonomous and flexible role where you will be trusted with key tasks.
An opportunity to have a real impact and be part of a company with purpose.
- Manages the delivery of large, complex Data Science projects using appropriate frameworks and collaborating with stake holders to manage scope and risk. Help the AI/ML Solution
- Analyst to build solution as per customer need on our platform Newgen AI Cloud. Drives profitability and continued success by managing service quality and cost and leading delivery. Proactively support sales through innovative solutions and delivery excellence.
Work location: Gurugram
1 Collaborate/contribute to all project phases, technical know to design, develop solutions and deploy at customer end.
2 End-to-end implementations i.e. gathering requirements, analysing, designing, coding, deployment to Production
3 Client facing role talking to client on regular basis to get requirement clarification
4. Lead the team
Core Tech Skills: Azure, Cloud Computing, Java/Scala, Python, Design Patterns and fair knowledge of Data Science. Fair Knowledge of Data Lake/DWH
Educational Qualification: Engineering graduate preferably Computer since graduate
Lead Machine Learning Engineer
IDfy is ranked amongst the World's Top 100 Regulatory Technology companies for the last two years. IDfy's AI-powered technology solutions help real people unlock real opportunities. We create the confidence required for people and businesses to engage with each other in the digital world. If you have used any major payment wallets, digitally opened a bank account , have used a self-drive car, have played a real-money online game, or hosted people through AirBnB, it's quite likely that your identity has been verified through IDfy at some point.
About the team
- The machine learning team is a closely knit team responsible for building models and services that support key workflows for IDfy.
- Our models are critical for these workflows and as such are expected to perform accurately and with low latency. We use a mix of conventional and hand-crafted deep learning models.
- The team comes from diverse backgrounds and experience. We respect opinions and believe in honest, open communication.
- 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.
About the role
In this role you will:
- Work on all aspects of a production machine learning platform: 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
While the emphasis will be on researching, building and deploying models into production, you will be expected to contribute to aspects mentioned above.
- You are a seasoned machine learning engineer (or data scientist). Our ideal candidate is someone with 8+ years of experience in production machine learning.
- You should be experienced in framing and solving complex problems with the application of machine learning or deep learning models.
- Deep expertise in computer vision or NLP with the experience of putting it into production at scale.
- You have experienced that and understand that modelling is only a small part of building and delivering AI solutions and know what it takes to keep a high-performance system up and running.
- Managing a large scale production ML system for at least a couple of years
- Optimization and tuning of models for deployment at scale
- Monitoring and debugging of production ML systems
- An enthusiasm and drive to learn, assimilate and disseminate the state of the art research. A lot of what we are building will require innovative approaches using newly researched models and applications.
- Past experience of mentoring junior colleagues
- Knowledge of and experience in ML Ops and tooling for efficient machine learning processes
Good to Have
- Our stack also includes languages like Go and Elixir. We would love it if you know any of these or take interest in functional programming.
- We use Docker and Kubernetes for deploying our services, so an understanding of this would be useful to have.
- Experience in using any other platform, frameworks, tools.
Other things to keep in mind
- Our goal is to help a significant part of the world’s population unlock real opportunities. This is an opportunity to make a positive impact here, and we hope you like it as much as we do.
Life At IDfy
People at IDfy care about creating value. We take pride in the strong collaborative culture that we have built, and our love for solving challenging problems. Life at IDfy is not always what you’d expect at a tech start-up that’s growing exponentially every quarter. There’s still time and space for balance.
We host regular talks, events and performances around Life, Art, Sports, and Technology; continuously sparking creative neurons in our people to keep their intellectual juices flowing. There’s never a dull day at IDfy. The office environment is casual and it goes beyond just the dress code. We have no conventional hierarchies and believe in an open-door policy where everyone is approachable.
GreedyGame is looking for a Business Analyst to join its clan. We are looking to get an enthusiastic Business Analyst who likes to play with Data. You'll be building insights from Data, creating analytical dashboard and monitoring KPI values. Also you will coordinate with teams working on different layers of the infrastructure.
Seniority Level: Associate
Level Industry: Marketing & Advertising
Employment Type: Full Time
Job Location: Bangalore
Experience: 1-2 years
WHAT ARE WE LOOKING FOR?
- Excellent planning, organizational, and time management skills.
- Exceptional analytical and conceptual thinking skills.
- A previous experience of working closely with Operations and Product Teams.
- Competency in Excel and SQL is a must.
- Experience with a programming language like Python is required.
- Knowledge of Marketing Tools is preferable.
WHAT WILL BE YOUR RESPONSIBILITIES?
- Evaluating business processes, anticipating requirements, uncovering areas for improvement, developing and implementing solutions.
- Should be able to generate meaningful insights to help the marketing team and product team in enhancing the user experience for Mobile and Web Apps.
- Leading ongoing reviews of business processes and developing optimization strategies.
- Performing requirements analysis from a user and business point of view
- Combining data from multiple sources like SQL tables, Google Analytics, Inhouse Analytical signals etc and driving relevant insights
- Deciding the success metrics and KPIs for different Products and features and making sure they are achieved.
- Act as quality assurance liaison prior to the release of new data analysis or application.
Skills and Abilities:
- Business Analytics
WHAT'S IN IT FOR YOU?
- An opportunity to be a part of a fast scaling start-up in the AdTech space that offers unmatched services and products.
- To work with a team of young enthusiasts who are always upbeat and self-driven to achieve bigger milestones in shorter time spans.
- A workspace that is wide open as per the open door policy at the company, located in the most happening center of Bangalore.
- A well-fed stomach makes the mind work better and therefore we provide - free lunch with a wide variety on all days of the week, a stocked-up pantry to satiate your want for munchies, a Foosball table to burst stress and above all a great working environment.
- We believe that we grow as you grow. Once you are a part of our team, your growth also becomes essential to us, and in order to make sure that happens, there are timely formal and informal feedbacks given
- Identify complex business problems and work towards building analytical solutions in-order to create large business impact.
- Demonstrate leadership through innovation in software and data products from ideation/conception through design, development and ongoing enhancement, leveraging user research techniques, traditional data tools, and techniques from the data science toolkit such as predictive modelling, NLP, statistical analysis, vector space modelling, machine learning etc.
- Collaborate and ideate with cross-functional teams to identify strategic questions for the business that can be solved and champion the effectiveness of utilizing data, analytics, and insights to shape business.
- Contribute to company growth efforts, increasing revenue and supporting other key business outcomes using analytics techniques.
- Focus on driving operational efficiencies by use of data and analytics to impact cost and employee efficiency.
- Baseline current analytics capability, ensure optimum utilization and continued advancement to stay abridge with industry developments.
- Establish self as a strategic partner with stakeholders, focused on full innovation system and fully supportive of initiatives from early stages to activation.
- Review stakeholder objectives and team's recommendations to ensure alignment and understanding.
- Drive analytics thought leadership and effectively contributes towards transformational initiatives.
- Ensure accuracy of data and deliverables of reporting employees with comprehensive policies and processes.
Role and Responsibilities
- Execute data mining projects, training and deploying models over a typical duration of 2 -12 months.
- The ideal candidate should be able to innovate, analyze the customer requirement, develop a solution in the time box of the project plan, execute and deploy the solution.
- Integrate the data mining projects embedded data mining applications in the FogHorn platform (on Docker or Android).
Candidates must meet ALL of the following qualifications:
- Have analyzed, trained and deployed at least three data mining models in the past. If the candidate did not directly deploy their own models, they will have worked with others who have put their models into production. The models should have been validated as robust over at least an initial time period.
- Three years of industry work experience, developing data mining models which were deployed and used.
- Programming experience in Python is core using data mining related libraries like Scikit-Learn. Other relevant Python mining libraries include NumPy, SciPy and Pandas.
- Data mining algorithm experience in at least 3 algorithms across: prediction (statistical regression, neural nets, deep learning, decision trees, SVM, ensembles), clustering (k-means, DBSCAN or other) or Bayesian networks
Any of the following extra qualifications will make a candidate more competitive:
- Soft Skills
- Sets expectations, develops project plans and meets expectations.
- Experience adapting technical dialogue to the right level for the audience (i.e. executives) or specific jargon for a given vertical market and job function.
- Technical skills
- Commonly, candidates have a MS or Ph.D. in Computer Science, Math, Statistics or an engineering technical discipline. BS candidates with experience are considered.
- Have managed past models in production over their full life cycle until model replacement is needed. Have developed automated model refreshing on newer data. Have developed frameworks for model automation as a prototype for product.
- Training or experience in Deep Learning, such as TensorFlow, Keras, convolutional neural networks (CNN) or Long Short Term Memory (LSTM) neural network architectures. If you don’t have deep learning experience, we will train you on the job.
- Shrinking deep learning models, optimizing to speed up execution time of scoring or inference.
- OpenCV or other image processing tools or libraries
- Cloud computing: Google Cloud, Amazon AWS or Microsoft Azure. We have integration with Google Cloud and are working on other integrations.
- Decision trees like XGBoost or Random Forests is helpful.
- Complex Event Processing (CEP) or other streaming data as a data source for data mining analysis
- Time series algorithms from ARIMA to LSTM to Digital Signal Processing (DSP).
- Bayesian Networks (BN), a.k.a. Bayesian Belief Networks (BBN) or Graphical Belief Networks (GBN)
- Experience with PMML is of interest (see www.DMG.org).
- Vertical experience in Industrial Internet of Things (IoT) applications:
- Energy: Oil and Gas, Wind Turbines
- Manufacturing: Motors, chemical processes, tools, automotive
- Smart Cities: Elevators, cameras on population or cars, power grid
- Transportation: Cars, truck fleets, trains
About FogHorn Systems
FogHorn is a leading developer of “edge intelligence” software for industrial and commercial IoT application solutions. FogHorn’s Lightning software platform brings the power of advanced analytics and machine learning to the on-premise edge environment enabling a new class of applications for advanced monitoring and diagnostics, machine performance optimization, proactive maintenance and operational intelligence use cases. FogHorn’s technology is ideally suited for OEMs, systems integrators and end customers in manufacturing, power and water, oil and gas, renewable energy, mining, transportation, healthcare, retail, as well as Smart Grid, Smart City, Smart Building and connected vehicle applications.
- 2019 Edge Computing Company of the Year – Compass Intelligence
- 2019 Internet of Things 50: 10 Coolest Industrial IoT Companies – CRN
- 2018 IoT Planforms Leadership Award & Edge Computing Excellence – IoT Evolution World Magazine
- 2018 10 Hot IoT Startups to Watch – Network World. (Gartner estimated 20 billion connected things in use worldwide by 2020)
- 2018 Winner in Artificial Intelligence and Machine Learning – Globe Awards
- 2018 Ten Edge Computing Vendors to Watch – ZDNet & 451 Research
- 2018 The 10 Most Innovative AI Solution Providers – Insights Success
- 2018 The AI 100 – CB Insights
- 2017 Cool Vendor in IoT Edge Computing – Gartner
- 2017 20 Most Promising AI Service Providers – CIO Review
Our Series A round was for $15 million. Our Series B round was for $30 million October 2017. Investors include: Saudi Aramco Energy Ventures, Intel Capital, GE, Dell, Bosch, Honeywell and The Hive.
About the Data Science Solutions team
In 2018, our Data Science Solutions team grew from 4 to 9. We are growing again from 11. We work on revenue generating projects for clients, such as predictive maintenance, time to failure, manufacturing defects. About half of our projects have been related to vision recognition or deep learning. We are not only working on consulting projects but developing vertical solution applications that run on our Lightning platform, with embedded data mining.
Our data scientists like our team because:
- We care about “best practices”
- Have a direct impact on the company’s revenue
- Give or receive mentoring as part of the collaborative process
- Questions and challenging the status quo with data is safe
- Intellectual curiosity balanced with humility
- Present papers or projects in our “Thought Leadership” meeting series, to support continuous learning