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About Moative
Moative, an Applied AI Services company, designs AI roadmaps, builds co-pilots and predictive AI solutions for companies in energy, utilities, packaging, commerce, and other primary industries. Through Moative Labs, we aspire to build micro-products and launch AI startups in vertical markets.
Our Past: We have built and sold two companies, one of which was an AI company. Our founders and leaders are Math PhDs, Ivy League University Alumni, Ex-Googlers, and successful entrepreneurs.Ā
Role
We seek skilled and experienced data science/machine learning professionals with a strong background in at least one of mathematics, nancial engineering, and electrical engineering, to join our Energy & Utilities team. If you are interested in articial intelligence, excited about solving real business problems in the energy and utilities industry, and keen to contribute to impactful projects, this role is for you!
Work youāll do
As a data scientist in the energy and utilities industry, you will perform quantitative analysis and build mathematical models to forecast energy demand, supply and strategies of ecient load balancing. You will work on models for short term and long term pricing, improving operational eciency, reducing costs, and ensuring reliable power supply. Youāll work closely with cross-functional teams to deploy these models in solutions that provide insights/ solutions to real-world business problems. You will also be involved in conducting experiments, building POCs and prototypes.
Responsibilities
- Develop and implement quantitative models for load forecasting, energy production and distribution optimization.
- Analyze historical data to identify and predict extreme events, and measure impact of extreme events. Enhance existing pricing and risk management frameworks.
- Develop and implement quantitative models for energy pricing and risk management. Monitor market conditions and adjust models as needed to ensure accuracy and effectiveness.
- Collaborate with engineering and operations teams to provide quantitative support for energy projects. Enhance existing energy management systems and develop new strategies for energy conservation.
- Maintain and improve quantitative tools and software used in energy management.
- Support end-to-end ML/ AI model lifecycle - from data preparation, data analysis and feature engineering to model development, validation and deployment
- Collaborate with domain experts, engineers, and stakeholders in translating business problems into data-driven solutions
- Document methodologies and results, present ndings and communicate insights to non-technical audiences
Skills & Requirements
- Strong background in mathematics, econometrics, electrical engineering, or a related eld.
- Experience data analysis, and quantitative modeling using programming languages such as Python or R.
- Excellent analytical and problem-solving skills.
- Strong understanding and experience with data analysis, statistical and mathematical concepts and ML algorithms
- Proficiency in Python and familiarity with basic Python libraries for data analysis and ML algorithms (such as NumPy, Pandas, ScikitLearn, NLTK).
- Strong communication skills
- Strong collaboration skills, ability to work with engineering and operations teams.
- A continuous learning attitude and a problem solving mind-set
Good to have -
- Knowledge of energy markets, regulations, and utility operation.
- Working knowledge of cloud platforms (e.g., AWS, Azure, GCP).
- Broad understanding of data structures and data engineering.
Working at Moative
Moative is a young company, but we believe strongly in thinking long-term, while acting with urgency. Our ethos is rooted in innovation, eciency and high-quality outcomes. We believe the future of work is AI-augmented and boundary less. Here are some of our guiding principles:
- Think in decades. Act in hours. As an independent company, our moat is time. While our decisions are for the long-term horizon, our execution will be fast ā measured in hours and days, not weeks and months.
- Own the canvas. Throw yourself in to build, x or improve ā anything that isnāt done right, irrespective of who did it. Be selsh about improving across the organization ā because once the rot sets in, we waste years in surgery and recovery.
- Use data or donāt use data. Use data where you ought to but not as a ācover-my-backā political tool. Be capable of making decisions with partial or limited data. Get better at intuition and pattern-matching. Whichever way you go, be mostly right about it.
- Avoid work about work. Process creeps on purpose, unless we constantly question it. We are deliberate about committing to rituals that take time away from the actual work. We truly believe that a meeting that could be an email, should be an email and you donāt need a person with the highest title to say that loud.
- High revenue per person. We work backwards from this metric. Our default is to automate instead of hiring. We multi-skill our people to own more outcomes than hiring someone who has less to do. We donāt like squatting and hoarding that comes in the form of hiring for growth. High revenue per person comes from high quality work from everyone. We demand it.
If this role and our work is of interest to you, please apply here. We encourage you to apply even if you believe you do not meet all the requirements listed above.
That said, you should demonstrate that you are in the 90th percentile or above. This may mean that you have studied in top-notch institutions, won competitions that are intellectually demanding, built something of your own, or rated as an outstanding performer by your current or previous employers.
The position is based out of Chennai. Our work currently involves significant in-person collaboration and we expect you to work out of our offices in Chennai.
Role Overview:
We are seeking a highly skilled and motivated Data Scientist to join our growing team. The ideal candidate will be responsible for developing and deploying machine learning models from scratch to production level, focusing on building robust data-driven products. You will work closely with software engineers, product managers, and other stakeholders to ensure our AI-driven solutions meet the needs of our users and align with the company's strategic goals.
Key Responsibilities:
- Develop, implement, and optimize machine learning models and algorithms to support product development.
- Work on the end-to-end lifecycle of data science projects, including data collection, preprocessing, model training, evaluation, and deployment.
- Collaborate with cross-functional teams to define data requirements and product taxonomy.
- Design and build scalable data pipelines and systems to support real-time data processing and analysis.
- Ensure the accuracy and quality of data used for modeling and analytics.
- Monitor and evaluate the performance of deployed models, making necessary adjustments to maintain optimal results.
- Implement best practices for data governance, privacy, and security.
- Document processes, methodologies, and technical solutions to maintain transparency and reproducibility.
Qualifications:
- Bachelor's or Master's degree in Data Science, Computer Science, Engineering, or a related field.
- 5+ years of experience in data science, machine learning, or a related field, with a track record of developing and deploying products from scratch to production.
- Strong programming skills in Python and experience with data analysis and machine learning libraries (e.g., Pandas, NumPy, TensorFlow, PyTorch).
- Experience with cloud platforms (e.g., AWS, GCP, Azure) and containerization technologies (e.g., Docker).
- Proficiency in building and optimizing data pipelines, ETL processes, and data storage solutions.
- Hands-on experience with data visualization tools and techniques.
- Strong understanding of statistics, data analysis, and machine learning concepts.
- Excellent problem-solving skills and attention to detail.
- Ability to work collaboratively in a fast-paced, dynamic environment.
Preferred Qualifications:
- Knowledge of microservices architecture and RESTful APIs.
- Familiarity with Agile development methodologies.
- Experience in building taxonomy for data products.
- Strong communication skills and the ability to explain complex technical concepts to non-technical stakeholders.
Job Description ā Data Science Ā
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Basic Qualification:
- ME/MS from premier institute with a background in Mechanical/Industrial/Chemical/Materials engineering.
- Strong Analytical skills and application of Statistical techniques to problem solving
- Expertise in algorithms, data structures and performance optimization techniques
- Proven track record of demonstrating end to end ownership involving taking an idea from incubator to market
- Ā Ā Minimum years of experience in data analysis (2+), statistical analysis, data mining, algorithms for optimization.
Responsibilities
The Data Engineer/Analyst will
- Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
- Clear interaction with Business teams including product planning, sales, marketing, finance for defining the projects, objectives.
- Mine and analyze data from company databases to drive optimization and improvement of product and process development, marketing techniques and business strategies
- Coordinate with different R&D and Business teams to implement models and monitor outcomes.
- Mentor team members towards developing quick solutions for business impact.
- Skilled at all stages of the analysis process including defining key business questions, recommending measures, data sources, methodology and study design, dataset creation, analysis execution, interpretation and presentation and publication of results.
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- 4+ yearsā experience in MNC environment with projects involving ML, DL and/or DS
- Experience in Machine Learning, Data Mining or Machine Intelligence (Artificial Intelligence)
- Knowledge on Microsoft Azure will be desired.
- Expertise in machine learning such as Classification, Data/Text Mining, NLP, Image Processing, Decision Trees, Random Forest, Neural Networks, Deep Learning Algorithms
- Proficient in Python and its various libraries such as Numpy, MatPlotLib, Pandas
- Superior verbal and written communication skills, ability to convey rigorous mathematical concepts and considerations to Business Teams.
- Experience in infra development / building platforms is highly desired.
- A drive to learn and master new technologies and techniques.
Do you want to help build real technology for a meaningful purpose? Do you want to contribute to making the world more sustainable, advanced and accomplished extraordinary precision in Analytics?Ā
What is your role?
As a Computer Vision & Machine Learning Engineer at Datasee.AI, youāll be core to the development of our robotic harvesting systemās visual intelligence. Youāll bring deep computer vision, machine learning, and software expertise while also thriving in a fast-paced, flexible, and energized startup environment. As an early team member, youāll directly build our success, growth, and culture. Youāll hold a significant role and are excited to grow your role as Datasee.AI grows.Ā
What youāll do
- You will be working with the core R&D team which drives the computer vision and image processing development.Ā
- Build deep learning model for our data and object detection on large scale images.Ā
- Design and implement real-time algorithms for object detection, classification, tracking, and segmentationĀ
- Coordinate and communicate within computer vision, software, and hardware teams to design and execute commercial engineering solutions.Ā
- Automate the workflow process between the fast-paced data delivery systems.Ā
What we are looking for
- 1 to 3+ years of professional experience in computer vision and machine learning.
- Extensive use of PythonĀ
- Experience in python libraries such as OpenCV, Tensorflow and NumpyĀ
- Familiarity with a deep learning library such as Keras and PyTorchĀ
- Worked on different CNN architectures such as FCN, R-CNN, Fast R-CNN and YOLO
- Experienced in hyperparameter tuning, data augmentation, data wrangling, model optimization and model deployment
- B.E./M.E/M.Sc. Computer Science/Engineering or relevant degree
- Dockerization, AWS modules and Production level modelling
- Basic knowledge of the Fundamentals of GIS would be added advantage
Prefered Requirements
- Experience with Qt, Desktop application development, Desktop AutomationĀ
- Knowledge on Satellite image processing, Geo-Information System, GDAL, Qgis and ArcGIS
About Datasee.AI:
Datasee>AI, Inc. is an AI driven Image Analytics company offering Asset Management solutions for industries in the sectors of Renewable Energy, Infrastructure, Utilities & Agriculture. With core expertise in Image processing, Computer Vision & Machine Learning, Takvaviyaās solution provides value across the enterprise for all the stakeholders through a data driven approach.Ā
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With Sales & Operations based out of US, Europe & India, Datasee.AI is a team of 32 people located across different geographies and with varied domain expertise and interests.Ā
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A focused and happy bunch of people who take tasks head-on and build scalable platforms and products.
A Reputed Analytics Consulting Company in Data Science field
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Job Title : Analyst / Sr. Analyst ā Data Science Developer - Python
Exp : 2 to 5 yrs
Loc : Bālore / Hyd / Chennai
NP: Candidate should join us in 2 months (Max) / Immediate Joiners Pref.
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About the role: Ā We are looking for an Analyst / Senior Analyst who works in the analytics domain with a strong python background. Ā Desired Skills, Competencies & Experience: Ā ā¢Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā ā¢ 2-4 years of experience in working in the analytics domain with a strong python background. ā¢Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā ā¢ Visualization skills in python with plotly, matplotlib, seaborn etc. Ability to create customized plots using such tools. ā¢Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā ā¢ Ability to write effective, scalable and modular code. Should be able to understand, test and debug existing python project modules quickly and contribute to that. ā¢Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā ā¢ Should be familiarized with Git workflows. Ā Good to Have: ā¢Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā ā¢ Familiarity with cloud platforms like AWS, AzureML, Databricks, GCP etc. ā¢Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā ā¢ Understanding of shell scripting, python package development. ā¢Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā ā¢ Experienced with Python data science packages like Pandas, numpy, sklearn etc. ā¢Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā ā¢ ML model building and evaluation experience using sklearn. Ā |