Sigmoid Analytics is a leading Data solutions company backed by Sequoia Capital. We offer best in- end-to-end data value chain spanning across Data Science, Data Engineering and Data Ops. With data and technology at the core of our solutions, we are solving some of the toughest problems out there. Our culture is modelled around expertise and mutual respect with a team first mindset. You’ll work with teams that push the boundaries of what-is-possible and build solutions that energize and inspire.
Offices: New York | Dallas | San Francisco | Lima | Bengaluru
The below role is for our Bengaluru office.
About the Role:
You will work on a broad range of cutting-edge data science and machine learning problems across a variety of industries. You will be engaging with clients to understand their business context. If you are passionate to work on complex unstructured business problems that can be solved using data science and machine learning we would like to talk to you.
Function: Data Science and Analysis → Data Science / Machine Learning
Desired Skills & Competencies:
- Strong learning acumen
- Team Management
- High sense of ownership
- Ability to work in a fast-paced and deadline-driven environment
- Loves technology
- Highly skilled at Data Interpretation
- Problem solver
- Good exposure to machine learning concepts and algorithms
- Must be fluent with any one of Python, R, Java
- Strong in statistical & machine learning concepts
- Knowledge of Python Libraries - SciPy, NumPy, Pandas, I Python, Scikit-learn
- Knowledge of distributed big data processing (PySpark, Jupyter, Linux, AWS)
Responsibilities:
- Hypothesis testing, insights generation, root cause analysis, factor analysis
- Statistical model (predictive & prescriptive) development using various statistical & machine learning techniques/algorithms
- Test/train the model, Improve Model accuracy, Monitor model performance
- Data Extraction from EDW/Big Data Platform, Dataset Preparation (creation of base data, aggregation, transformation), performing EDA
Desired Experience & Education:
- 3 - 5 years of relevant Machine Learning experience.
- B. Tech from Tier-1 college / M.S or M. Tech is preferred in Computer Science, Information Technology, or similar degree.
Note:
By submitting your application, you consent to being contacted by our Talent Acquisition team via phone call, email, SMS, WhatsApp, or other communication channels regarding your application and relevant career opportunities.Skills Required
- 3–5 years of relevant machine learning experience
- Fluency in at least one of Python, R, or Java
- Strong statistical and machine learning concepts
- Knowledge of SciPy, NumPy, Pandas, IPython, and Scikit-learn
- Knowledge of distributed big data processing using PySpark, Jupyter, Linux, and AWS
- B.Tech from a Tier-1 college, or M.S. or M.Tech in Computer Science, Information Technology, or a similar discipline
What We Do
Sigmoid is a leading data engineering and AI solutions company that helps enterprises gain a competitive advantage with effective data-driven decision-making. Our team is strongly driven by the passion to unravel data complexities. We generate actionable insights and translate them into successful business strategies. We leverage our expertise in open-source and cloud technologies to develop innovative frameworks catering to specific customer needs. Our unique approach has positively influenced the business performance of our Fortune 500 clients across CPG, retail, banking, financial services, manufacturing, and other verticals. Backed by Sequoia Capital, Sigmoid has offices in New York, San Francisco, Dallas, Lima, Amsterdam, and Bengaluru. We are recognized among the world's fastest growing and innovative tech companies, winning several awards and recognition like the Deloitte Technology Fast 500, Financial Times- The Americas’ Fastest Growing Companies, Inc. 5000, Great Place To Work- India’s Best Leaders in Times of Crisis, Data Breakthrough, Aegis Graham Bell, TiE50, NASSCOM Emerge 50, and others. Learn more: https://www.sigmoid.com/ or https://sigmoid.com/careers/ for careers.
