- You hold an MS/Ph.D. degree in a STEM domain and 5+ years in a relevant position
- You share your ideas and continuously improve yourself and the team around you.
- Experienced in building and scaling data teams across multiple locations and domains.
- You have a good understanding of evolving an organization’s culture based on analytics and data insights
- Natural and comfortable leader, have excellent problem-solving, organizational, and analytical skills
- Passionate about data improving business and engineering practices like continuous delivery, traceability, and observability
- Strong communication skills, high integrity, and great attention to detail
You’ll get to work with:
- Consumer-facing, as well as core platform, finance, and distribution business units
- Marketing and product teams, across to our engineering teams
- Modern infrastructure (Kubernetes, AWS, GCP)
What we offer
- We offer you a chance to be part of a truly amazing journey in a company that sets very high targets and works hard to achieve them. You will be able to work with smart, motivated, and engaged co-workers from all over the world, in an intense and very energetic environment. This leads to you having a tangible impact on the way that we operate and expand our business.
Some of the highlights of the package include:
- Strong technical culture of continuous innovation and improvement
- Chance to become a shareholder of Gelato!
- Flexible festive holidays, swap days off according to your values and beliefs.
- Work at one of our hub city offices or even remotely
- And much more!
About The creator economy with local production. ( GE1)
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- 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
Key Responsibilities:
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
- Working closely with business stakeholders to define, strategize and execute crucial business problem statements which lie at the core of improvising current and future data-backed product offerings.
- Building and refining underwriting models for extending credit to sellers and API Partners in collaboration with the lending team
- Conceiving, planning and prioritizing data projects and manage timelines
- Building analytical systems and predictive models as a part of the agile ecosystem
- Testing performance of data-driven products participating in sprint-wise feature releases
- Managing a team of data scientists and data engineers to develop, train and test predictive models
- Managing collaboration with internal and external stakeholders
- Building data-centric culture from within, partnering with every team, learning deeply about business, working with highly experienced, sharp and insanely ambitious colleagues
What you need to have:
- B.Tech/ M.Tech/ MS/ PhD in Data Science / Computer Science, Statistics, Mathematics & Computation with a demonstrated skill-set in leading an Analytics and Data Science team from IIT, BITS Pilani, ISI
- 8+ years working in the Data Science and analytics domain with 3+ years of experience in leading a data science team to understand the projects to be prioritized, how the team strategy aligns with the organization mission;
- Deep understanding of credit risk landscape; should have built or maintained underwriting models for unsecured lending products
- Should have handled a leadership team in a tech startup preferably a fintech/ lending/ credit risk startup.
- We value entrepreneurship spirit: if you have had the experience of starting your own venture - that is an added advantage.
- Strategic thinker with agility and endurance
- Aware of the latest industry trends in Data Science and Analytics with respect to Fintech, Digital Transformations and Credit-lending domain
- Excellent command over communication is the key to manage multiple stakeholders like the leadership team, product teams, existing & new investors.
- Cloud Computing, Python, SQL, ML algorithms, Analytics and problem - solving mindset
- Knowledge and demonstrated skill-sets in AWS
About the Company
Blue Sky Analytics is a Climate Tech startup that combines the power of AI & Satellite data to aid in the creation of a global environmental data stack. Our funders include Beenext and Rainmatter. Over the next 12 months, we aim to expand to 10 environmental data-sets spanning water, land, heat, and more!
We are looking for a data scientist to join its growing team. This position will require you to think and act on the geospatial architecture and data needs (specifically geospatial data) of the company. This position is strategic and will also require you to collaborate closely with data engineers, data scientists, software developers and even colleagues from other business functions. Come save the planet with us!
Your Role
Manage: It goes without saying that you will be handling large amounts of image and location datasets. You will develop dataframes and automated pipelines of data from multiple sources. You are expected to know how to visualize them and use machine learning algorithms to be able to make predictions. You will be working across teams to get the job done.
Analyze: You will curate and analyze vast amounts of geospatial datasets like satellite imagery, elevation data, meteorological datasets, openstreetmaps, demographic data, socio-econometric data and topography to extract useful insights about the events happening on our planet.
Develop: You will be required to develop processes and tools to monitor and analyze data and its accuracy. You will develop innovative algorithms which will be useful in tracking global environmental problems like depleting water levels, illegal tree logging, and even tracking of oil-spills.
Demonstrate: A familiarity with working in geospatial libraries such as GDAL/Rasterio for reading/writing of data, and use of QGIS in making visualizations. This will also extend to using advanced statistical techniques and applying concepts like regression, properties of distribution, and conduct other statistical tests.
Produce: With all the hard work being put into data creation and management, it has to be used! You will be able to produce maps showing (but not limited to) spatial distribution of various kinds of data, including emission statistics and pollution hotspots. In addition, you will produce reports that contain maps, visualizations and other resources developed over the course of managing these datasets.
Requirements
These are must have skill-sets that we are looking for:
- Excellent coding skills in Python (including deep familiarity with NumPy, SciPy, pandas).
- Significant experience with git, GitHub, SQL, AWS (S3 and EC2).
- Worked on GIS and is familiar with geospatial libraries such as GDAL and rasterio to read/write the data, a GIS software such as QGIS for visualisation and query, and basic machine learning algorithms to make predictions.
- Demonstrable experience implementing efficient neural network models and deploying them in a production environment.
- Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
- Capable of writing clear and lucid reports and demystifying data for the rest of us.
- Be curious and care about the planet!
- Minimum 2 years of demonstrable industry experience working with large and noisy datasets.
Benefits
- Work from anywhere: Work by the beach or from the mountains.
- Open source at heart: We are building a community where you can use, contribute and collaborate on.
- Own a slice of the pie: Possibility of becoming an owner by investing in ESOPs.
- Flexible timings: Fit your work around your lifestyle.
- Comprehensive health cover: Health cover for you and your dependents to keep you tension free.
- Work Machine of choice: Buy a device and own it after completing a year at BSA.
- Quarterly Retreats: Yes there's work-but then there's all the non-work+fun aspect aka the retreat!
- Yearly vacations: Take time off to rest and get ready for the next big assignment by availing the paid leaves.
Tiger Analytics is a global AI & analytics consulting firm. With data and technology at the core of our solutions, we are solving some of the toughest problems out there. Our culture is modeled around expertise and mutual respect with a team first mindset. Working at Tiger, you’ll be at the heart of this AI revolution. You’ll work with teams that push the boundaries of what-is-possible and build solutions that energize and inspire.
We are headquartered in the Silicon Valley and have our delivery centres across the globe. The below role is for our Chennai or Bangalore office, or you can choose to work remotely.
About the Role:
As an Associate Director - Data Science at Tiger Analytics, you will lead data science aspects of endto-end client AI & analytics programs. Your role will be a combination of hands-on contribution, technical team management, and client interaction.
• Work closely with internal teams and client stakeholders to design analytical approaches to
solve business problems
• Develop and enhance a broad range of cutting-edge data analytics and machine learning
problems across a variety of industries.
• Work on various aspects of the ML ecosystem – model building, ML pipelines, logging &
versioning, documentation, scaling, deployment, monitoring and maintenance etc.
• Lead a team of data scientists and engineers to embed AI and analytics into the client
business decision processes.
Desired Skills:
• High level of proficiency in a structured programming language, e.g. Python, R.
• Experience designing data science solutions to business problems
• Deep understanding of ML algorithms for common use cases in both structured and
unstructured data ecosystems.
• Comfortable with large scale data processing and distributed computing
• Excellent written and verbal communication skills
• 10+ years exp of which 8 years of relevant data science experience including hands-on
programming.
Designation will be commensurate with expertise/experience. Compensation packages among the best in the industry.
Responsibilities for Data Scientist/ NLP Engineer
Work with customers to identify opportunities for leveraging their data to drive business
solutions.
• 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
along with metrics to track their progress
Managing available resources such as hardware, data, and personnel so that deadlines
are met
Analysing the ML algorithms that could be used to solve a given problem and ranking
them by their success probability
Exploring and visualizing data to gain an understanding of it, then identifying
differences in data distribution that could affect performance when deploying the model
in the real world
Verifying data quality, and/or ensuring it via data cleaning
Supervising the data acquisition process if more data is needed
Defining validation strategies
Defining the pre-processing or feature engineering to be done on a given dataset
Defining data augmentation pipelines
Training models and tuning their hyper parameters
Analysing the errors of the model and designing strategies to overcome them
Deploying models to production
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).
Core Qualifications
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
Bonus Qualifications
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.
Press: https://www.foghorn.io/press-room/">https://www.foghorn.io/press-room/
Awards: https://www.foghorn.io/awards-and-recognition/">https://www.foghorn.io/awards-and-recognition/
- 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