About Busigence Technologies
Busigence is a Decision Intelligence Company. We create decision intelligence products for real people by combining data, technology, business, and behavior enabling strengthened decisions.
Scaling established startup by IIT alumni innovating & disrupting marketing domain through artificial intelligence. We bring those people onboard who are dedicated to deliver wisdom to humanity by solving the world's most pressing problems differently thereby significantly impacting thousands of souls, everyday.
We are a deep rooted organization with six years of success story having worked with folks from top tier background (IIT, NSIT, DCE, BITS, IIITs, NITs, IIMs, ISI etc.) maintaining an awesome culture with a common vision to build great data products.
In past we have served fifty five customers and presently developing our second product, Robonate . First was emmoQ - an emotion intelligence platform. Third offering, H2HData , an innovation lab where we solve hard problems through data, science, & design.
We work extensively & intensely on big data, data science, machine learning, deep learning, reinforcement learning, data analytics, natural language processing, cognitive computing, and business intelligence.
We try real hard to hire fun loving crazy folks who are driven by more than a paycheck. You shall be working with creamiest talent on extremely challenging problems at most happening workplace.
Our mission is to make the world decision intelligent. We envision to have worked on atleast 1% of worlds data by 2020.
Why Explore a Career at Busigence
This section should have been entitled - Why Explore a Challenge at Busigence. What?
Busigence is not for everyone. This is the strongest differentiator. How?
Skills are secondary for us. We believe in intentions, not capabilities. Why?
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If the above three are not understood and/or interest you, we would encourage you refrain applying to us. You won't be actually able to work with us.
80-85% candidates looks for a job in an open position. 85-98% forsee a career in it. Hardly 2% are able to realise it as a challenge, which may satisfy their soul.
We look for these 2%. PERIOD.
If you happen to be fortunately falling in this group then world is too small for you. Reason being there are very few organisations which can really meet your expectations.
We can! Busigence works on real hard problems. Solving customer's problem is our passion.
1. We do where world is moving. Artificial Intelligence. Real AI.
2. We are a real startup culture (this is not bean bags or open office or flexible hours. It is a spirit to create something which doesn't exist).
3. We hire creme de la creme. Coincidentally, it happens to be candidates from topmost tier (IIT & equivalent). People enjoy working with like minded people.
4. You will be empowered everyday and make you feel an entrepreneurial trait in you.
5. This will be Greatest Work of Your Life. Promise!
Busigence Interview Process
We don't hire, we handpick - Believe with us. Laugh with us. Work with us.
For formality,
Step 1 : Apply iff you meet Real Role's & Ideal You's
Step 2 : Round 0: First call followed by Application Form
Step 3 : Round 1: Technology/ Process/ Business Capability Evaluation
Step 4 : Round 2: Day Spent (1 or 2 days) working with us
Enough. We are Done.
Similar jobs
We at Thena are looking for a Machine Learning Engineer with 2-4 years of industry experience to join our team. The ideal candidate will be passionate about developing and deploying ML models that drive business value and have a strong background in ML Ops.
Responsibilities:
- Develop, fine-tune, and deploy ML models for B2B customer communication and collaboration use cases.
- Collaborate with cross-functional teams to define requirements, design models, and deploy them in production.
- Optimize model performance and accuracy through experimentation, iteration, and testing.
- Build and maintain ML infrastructure and tools to support model development and deployment.
- Stay up-to-date with the latest research and best practices in ML, and share knowledge with the team.
Qualifications:
- 2-4 years of industry experience in machine learning engineering, with a focus on natural language processing (NLP) and text classification models.
- Experience with ML Ops, including deploying and managing ML models in production environments.
- Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow.
- Experience with Embeddings and building on top of LLMs.
- Strong problem-solving and analytical skills, with the ability to develop creative solutions to complex problems.
- Strong communication skills, with the ability to collaborate effectively with cross-functional teams.
- Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related field.
- Create and maintain optimal data pipeline architecture
- Assemble large, complex data sets that meet business requirements
- Identifying, designing, and implementing internal process improvements including redesigning infrastructure for greater scalability, optimizing data delivery, and automating manual processes
- Work with Data, Analytics & Tech team to extract, arrange and analyze data
- Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS technologies
- Building analytical tools to utilize the data pipeline, providing actionable insight into key business performance metrics including operational efficiency and customer acquisition
- Works closely with all business units and engineering teams to develop a strategy for long-term data platform architecture.
- Working with stakeholders including data, design, product, and executive teams, and assisting them with data-related technical issues
- Working with stakeholders including the Executive, Product, Data, and Design teams to support their data infrastructure needs while assisting with data-related technical issues.
- SQL
- Ruby or Python(Ruby preferred)
- Apache-Hadoop based analytics
- Data warehousing
- Data architecture
- Schema design
- ML
- Prior experience of 2 to 5 years as a Data Engineer.
- Ability in managing and communicating data warehouse plans to internal teams.
- Experience designing, building, and maintaining data processing systems.
- Ability to perform root cause analysis on external and internal processes and data to identify opportunities for improvement and answer questions.
- Excellent analytic skills associated with working on unstructured datasets.
- Ability to build processes that support data transformation, workload management, data structures, dependency, and metadata.
Responsibilities:
- Design and develop strong analytics system and predictive models
- Managing a team of data scientists, machine learning engineers, and big data specialists
- Identify valuable data sources and automate data collection processes
- Undertake pre-processing of structured and unstructured data
- Analyze large amounts of information to discover trends and patterns
- Build predictive models and machine-learning algorithms
- Combine models through ensemble modeling
- Present information using data visualization techniques
- Propose solutions and strategies to business challenges
- Collaborate with engineering and product development teams
Requirements:
- Proven experience as a seasoned Data Scientist
- Good Experience in data mining processes
- Understanding of machine learning and Knowledge of operations research is a value addition
- Strong understanding and experience in R, SQL, and Python; Knowledge base with Scala, Java, or C++ is an asset
- Experience using business intelligence tools (e. g. Tableau) and data frameworks (e. g. Hadoop)
- Strong math skills (e. g. statistics, algebra)
- Problem-solving aptitude
- Excellent communication and presentation skills
- Experience in Natural Language Processing (NLP)
- Strong competitive coding skills
- BSc/BA in Computer Science, Engineering or relevant field; graduate degree in Data Science or other quantitative field is preferred
- Actively engage with internal business teams to understand their challenges and deliver robust, data-driven solutions.
- Work alongside global counterparts to solve data-intensive problems using standard analytical frameworks and tools.
- Be encouraged and expected to innovate and be creative in your data analysis, problem-solving, and presentation of solutions.
- Network and collaborate with a broad range of internal business units to define and deliver joint solutions.
- Work alongside customers to leverage cutting-edge technology (machine learning, streaming analytics, and ‘real’ big data) to creatively solve problems and disrupt existing business models.
In this role, we are looking for:
- A problem-solving mindset with the ability to understand business challenges and how to apply your analytics expertise to solve them.
- The unique person who can present complex mathematical solutions in a simple manner that most will understand, including customers.
- An individual excited by innovation and new technology and eager to finds ways to employ these innovations in practice.
- A team mentality, empowered by the ability to work with a diverse set of individuals.
Basic Qualifications
- A Bachelor’s degree in Data Science, Math, Statistics, Computer Science or related field with an emphasis on analytics.
- 5+ Years professional experience in a data scientist/analyst role or similar.
- Proficiency in your statistics/analytics/visualization tool of choice, but preferably in the Microsoft Azure Suite, including Azure ML Studio and PowerBI as well as R, Python, SQL.
Preferred Qualifications
- Excellent communication, organizational transformation, and leadership skills
- Demonstrated excellence in Data Science, Business Analytics and Engineering
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