5+ Predictive modelling Jobs in Chennai | Predictive modelling Job openings in Chennai

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. 

Role

We seek skilled and experienced data science/machine learning professionals with a strong background in at least one of mathematics, financial engineering, and electrical engineering, to join our Energy & Utilities team. If you are interested in artificial 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 you’ll 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 efficient load balancing. You will work on models for short term and long term pricing, improving operational efficiency, reducing costs, and ensuring reliable power supply. You’ll 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 findings 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, efficiency 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 – measured in hours and days, not weeks and months.
• Own the canvas. Throw yourself in to build, x or improve – anything that isn’t done right, irrespective of who did it. Be selfish about improving across the organization – because once the rot sets in, we waste years in surgery and recovery.
• Use data or don’t use data. Use data where you ought to but not as a ‘cover-my-back’ 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 don’t 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 don’t 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.

We are looking for an outstanding ML Architect (Deployments) with expertise in deploying Machine Learning solutions/models into production and scaling them to serve millions of customers. A candidate with an adaptable and productive working style which fits in a fast-moving environment.

Skills:

- 5+ years deploying Machine Learning pipelines in large enterprise production systems.

- Experience developing end to end ML solutions from business hypothesis to deployment / understanding the entirety of the ML development life cycle.
- Expert in modern software development practices; solid experience using source control management (CI/CD).
- Proficient in designing relevant architecture / microservices to fulfil application integration, model monitoring, training / re-training, model management, model deployment, model experimentation/development, alert mechanisms.
- Experience with public cloud platforms (Azure, AWS, GCP).
- Serverless services like lambda, azure functions, and/or cloud functions.
- Orchestration services like data factory, data pipeline, and/or data flow.
- Data science workbench/managed services like azure machine learning, sagemaker, and/or AI platform.
- Data warehouse services like snowflake, redshift, bigquery, azure sql dw, AWS Redshift.
- Distributed computing services like Pyspark, EMR, Databricks.
- Data storage services like cloud storage, S3, blob, S3 Glacier.
- Data visualization tools like Power BI, Tableau, Quicksight, and/or Qlik.
- Proven experience serving up predictive algorithms and analytics through batch and real-time APIs.
- Solid working experience with software engineers, data scientists, product owners, business analysts, project managers, and business stakeholders to design the holistic solution.
- Strong technical acumen around automated testing.
- Extensive background in statistical analysis and modeling (distributions, hypothesis testing, probability theory, etc.)
- Strong hands-on experience with statistical packages and ML libraries (e.g., Python scikit learn, Spark MLlib, etc.)
- Experience in effective data exploration and visualization (e.g., Excel, Power BI, Tableau, Qlik, etc.)
- Experience in developing and debugging in one or more of the languages Java, Python.
- Ability to work in cross functional teams.
- Apply Machine Learning techniques in production including, but not limited to, neuralnets, regression, decision trees, random forests, ensembles, SVM, Bayesian models, K-Means, etc.

Roles and Responsibilities:

Deploying ML models into production, and scaling them to serve millions of customers.

Technical solutioning skills with deep understanding of technical API integrations, AI / Data Science, BigData and public cloud architectures / deployments in a SaaS environment.

Strong stakeholder relationship management skills - able to influence and manage the expectations of senior executives.
Strong networking skills with the ability to build and maintain strong relationships with both business, operations and technology teams internally and externally.

Provide software design and programming support to projects.

 Qualifications & Experience:

Engineering and post graduate candidates, preferably in Computer Science, from premier institutions with proven work experience as a Machine Learning Architect (Deployments) or a similar role for 5-7 years.

Ganit has flipped the data science value chain as we do not start with a technique but for us, consumption comes first. With this philosophy, we have successfully scaled from being a small start-up to a 200 resource company with clients in the US, Singapore, Africa, UAE, and India. 

We are looking for experienced data enthusiasts who can make the data talk to them. 

You will: 

• Understand business problems and translate business requirements into technical requirements. 
• Conduct complex data analysis to ensure data quality & reliability i.e., make the data talk by extracting, preparing, and transforming it. 
• Identify, develop and implement statistical techniques and algorithms to address business challenges and add value to the organization. 
• Gather requirements and communicate findings in the form of a meaningful story with the stakeholders  
• Build & implement data models using predictive modelling techniques. Interact with clients and provide support for queries and delivery adoption. 
• Lead and mentor data analysts. 

We are looking for someone who has: 

• Apart from your love for data and ability to code even while sleeping you would need the following. 
• Minimum of 02 years of experience in designing and delivery of data science solutions. 
• You should have successful projects of retail/BFSI/FMCG/Manufacturing/QSR in your kitty to show-off. 
• Deep understanding of various statistical techniques, mathematical models, and algorithms to start the conversation with the data in hand. 
• Ability to choose the right model for the data and translate that into a code using R, Python, VBA, SQL, etc. 
• Bachelors/Masters degree in Engineering/Technology or MBA from Tier-1 B School or MSc. in Statistics or Mathematics 

Skillset Required:

• Regression
• Classification
• Predictive Modelling
• Prescriptive Modelling
• Python
• R
• Descriptive Modelling
• Time Series
• Clustering
•  

What is in it for you: 

• Be a part of building the biggest brand in Data science. 
• An opportunity to be a part of a young and energetic team with a strong pedigree. 
• Work on awesome projects across industries and learn from the best in the industry, while growing at a hyper rate. 

Please Note:  

At Ganit, we are looking for people who love problem solving. You are encouraged to apply even if your experience does not precisely match the job description above. Your passion and skills will stand out and set you apart—especially if your career has taken some extraordinary twists and turns over the years. We welcome diverse perspectives, people who think rigorously and are not afraid to challenge assumptions in a problem. Join us and punch above your weight! 

Ganit is an equal opportunity employer and is committed to providing a work environment that is free from harassment and discrimination. 

All recruitment, selection procedures and decisions will reflect Ganit’s commitment to providing equal opportunity. All potential candidates will be assessed according to their skills, knowledge, qualifications, and capabilities. No regard will be given to factors such as age, gender, marital status, race, religion, physical impairment, or political opinions. 

Ganit Inc. is the fastest growing Data Science & AI company in Chennai.

Founded in 2017, by 3 industry experts who are alumnus of IITs/SPJIMR with each of them having 17+ years of experience in the field of analytics.

We are in the business of maximising Decision Making Power (DMP) for companies by providing solutions at the intersection of hypothesis based analytics, discovery based AI and IoT. Our solutions are a combination of customised services and functional product suite.

We primarily operate as a US-based start-up and have clients across US, Asia-Pacific, Middle-East and have offices in USA - New Jersey & India - Chennai.

Started with 3 people, the company is fast growing with 100+ employees

1. What do we expect from you

- Should posses minimum 2 years of experience of data analytics model development and deployment

- Skills relating to core Statistics & Mathematics.

- Huge interest in handling numbers

- Ability to understand all domains in businesses across various sectors

- Natural passion towards numbers, business, coding, visualisation

2. Necessary skill set:

- Proficient in R/Python, Advanced Excel, SQL

- Should have worked with Retail/FMCG/CPG projects solving analytical problems in Sales/Marketing/Supply Chain functions

- Very good understanding of algorithms, mathematical models, statistical techniques, data mining, like Regression models, Clustering/ Segmentation, time series forecasting, Decision trees/Random forest, etc.

- Ability to choose the right model for the right data and translate that into code in R, Python, VBA (Proven capabilities)

- Should have handled large datasets and with through understanding of SQL

- Ability to handle a team of Data Analysts

3. Good to have skill set:

- Microsoft PowerBI / Tableau / Qlik View / Spotfire

4. Job Responsibilities:

- Translate business requirements into technical requirements

- Data extraction, preparation and transformation

- Identify, develop and implement statistical techniques and algorithms that address business challenges and adds value to the organisation

- Create and implement data models

- Interact with clients for queries and delivery adoption

5. Screening Methodology

- Problem Solving round (Telephonic Conversation)

- Technical discussion round (Telephonic Conversation)

- Final fitment discussion (Video Round