THE IDEAL CANDIDATE WILL
- Engage with executive level stakeholders from client's team to translate business problems to high level solution approach
- Partner closely with practice, and technical teams to craft well-structured comprehensive proposals/ RFP responses clearly highlighting Tredence’s competitive strengths relevant to Client's selection criteria
- Actively explore the client’s business and formulate solution ideas that can improve process efficiency and cut cost, or achieve growth/revenue/profitability targets faster
- Work hands-on across various MLOps problems and provide thought leadership
- Grow and manage large teams with diverse skillsets
- Collaborate, coach, and learn with a growing team of experienced Machine Learning Engineers and Data Scientists
- BE/BTech/MTech (Specialization/courses in ML/DS)
- At-least 7+ years of Consulting services delivery experience
- Very strong problem-solving skills & work ethics
- Possesses strong analytical/logical thinking, storyboarding and executive communication skills
- 5+ years of experience in Python/R, SQL
- 5+ years of experience in NLP algorithms, Regression & Classification Modelling, Time Series Forecasting
- Hands on work experience in DevOps
- Should have good knowledge in different deployment type like PaaS, SaaS, IaaS
- Exposure on cloud technologies like Azure, AWS or GCP
- Knowledge in python and packages for data analysis (scikit-learn, scipy, numpy, pandas, matplotlib).
- Knowledge of Deep Learning frameworks: Keras, Tensorflow, PyTorch, etc
- Experience with one or more Container-ecosystem (Docker, Kubernetes)
- Experience in building orchestration pipeline to convert plain python models into a deployable API/RESTful endpoint.
- Good understanding of OOP & Data Structures concepts
Nice to Have:
- Exposure to deployment strategies like: Blue/Green, Canary, AB Testing, Multi-arm Bandit
- Experience in Helm is a plus
- Strong understanding of data infrastructure, data warehouse, or data engineering
You can expect to –
- Work with world’ biggest retailers and help them solve some of their most critical problems. Tredence is a preferred analytics vendor for some of the largest Retailers across the globe
- Create multi-million Dollar business opportunities by leveraging impact mindset, cutting edge solutions and industry best practices.
- Work in a diverse environment that keeps evolving
- Hone your entrepreneurial skills as you contribute to growth of the organization
Specialism- Advance Analytics, Data Science, regression, forecasting, analytics, SQL, R, python, decision tree, random forest, SAS, clustering classification
Senior Analytics Consultant- Responsibilities
- Understand business problem and requirements by building domain knowledge and translate to data science problem
- Conceptualize and design cutting edge data science solution to solve the data science problem, apply design thinking concepts
- Identify the right algorithms , tech stack , sample outputs required to efficiently adder the end need
- Prototype and experiment the solution to successfully demonstrate the value
Independently or with support from team execute the conceptualized solution as per plan by following project management guidelines
- Present the results to internal and client stakeholder in an easy to understand manner with great story telling, story boarding, insights and visualization
- Help build overall data science capability for eClerx through support in pilots, pre sales pitches, product development , practice development initiatives
- 2 to 6 years of experience in imparting technical training/ mentoring
- Must have very strong concepts of Data Analytics
- Must have hands-on and training experience on Python, Advanced Python, R programming, SAS and machine learning
- Must have good knowledge of SQL and Advanced SQL
- Should have basic knowledge of Statistics
- Should be good in Operating systems GNU/Linux, Network fundamentals,
- Must have knowledge on MS office (Excel/ Word/ PowerPoint)
- Self-Motivated and passionate about technology
- Excellent analytical and logical skills and team player
- Must have exceptional Communication Skills/ Presentation Skills
- Good Aptitude skills is preferred
- Exceptional communication skills
- Ability to quickly learn any new technology and impart the same to other employees
- Ability to resolve all technical queries of students
- Conduct training sessions and drive the placement driven quality in the training
- Must be able to work independently without the supervision of a senior person
- Participate in reviews/ meetings
- UG: Any Graduate in IT/Computer Science, B.Tech/B.E. – IT/ Computers
- PG: MCA/MS/MSC – Computer Science
- Any Graduate/ Post graduate, provided they are certified in similar courses
EduBridge is an Equal Opportunity employer and we believe in building a meritorious culture where everyone is recognized for their skills and contribution.
Launched in 2009 EduBridge Learning is a workforce development and skilling organization with 50+ training academies in 18 States pan India. The organization has been providing skilled manpower to corporates for over 10 years and is a leader in its space. We have trained over a lakh semi urban & economically underprivileged youth on relevant life skills and industry-specific skills and provided placements in over 500 companies. Our latest product E-ON is committed to complementing our training delivery with an Online training platform, enabling the students to learn anywhere and anytime.
You can also visit us on https://www.facebook.com/Edubridgelearning/">Facebook , https://www.linkedin.com/company/edubridgelearning/">LinkedIn for our latest initiatives and products
As an experienced Data Scientist you’ll join a team of data scientists, analysts, and software engineers
working to push the boundaries of data science in health care. We like to experiment, iterate, and
innovate with technology, from developing new algorithms specific to health care’s challenges, to
bringing the latest machine learning practices and applications developed in other industries into the
health care world. We know that algorithms are only valuable when powered by the right data, so we
focus on fully understanding the problems we need to solve, and truly understanding the data behind
them before launching into solutions – ensuring that the solutions we do land on are impactful and
• Research, conceptualize, and implement analytical approaches and predictive modeling to
evaluate scenarios, predict utilization and clinical outcomes, and recommend actions to impact
• Manage and execute on the entire model development process, including scope definition,
hypothesis formation, data cleaning and preparation, feature selection, model implementation
in production, validation and iteration, using multiple data sources.
• Provide guidance on necessary data and software infrastructure capabilities to deliver a scalable
solution across partners and support the implementation of the team’s algorithms and models
• Contribute to the development and publication in major journals, conferences showcasing
leadership in healthcare data science.
• Work closely and collaborate with Data Scientists, Machine Learning engineers, IT teams and
Business stakeholders spread out across various locations in US and India to achieve business
• Provide guidance to other Data Scientist and Machine Learning Engineers
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
This will include:
The verticals included are: